Reconstructed Slice Thickness Research Articles

Coronary CT angiography using photon counting CT for the detection of coronary artery stenoses and coronary atherosclerotic plaque: comparison of reconstructions with 0.2 mm and 0.4 mm slice thickness

Abstract Photon Counting CT allows the acquisition of high-resolution data sets with 0.2 mm reconstructed slice thickness. It is unknown whether the detection of coronary artery stenoses, of coronary plaque or of vulnerable plaque characteristics is improved in data sets that employ maximum resolution. We therefore compared the identification of above characteristics in data sets reconstructed with 0.2 mm and 0.4 mm slice thickness In 30 patients with suspected coronary artery disease, sinus rhythm, a heart rate ≤65 beats/min, and body weight ≤ 100 kg, high-resolution data sets were acquired by photon counting CT (60 ml contrast i.v. at 6 ml/s) after s.c. application of nitrates in inspiratory breathhold. Data were reconstructed with 0.2 mm slice thickness at 0.1 mm increment and 0.4 mm slice thickness at 0.2 mm increment. Next to quantitative analysis of image quality parameters, all data sets were evaluated by two independent expert reviewers concerning subjective image quality as well as the ability to determine the presence of coronary artery stenoses, calcified and non- calcified plaque, as well as parameters of plaque vulnerability (positive remodeling, necrotic core, density < 30 HU and napkin-ring sign) using a 5-point Likert scale (-2 to +2) and a dedicated 11-segment coronary model. Of the 30 patients, 47% were male (mean age 58±12 years, mean heart rate 53±6 bpm, mean body weight 80±15 kg). The median dose length product was 508 mGy*cm. Mean image noise was 42±7 HU vs. 34±7 HU for 0.2 mm vs. 0.4 mm reconstructions (p < 0.001). The median image quality score was significantly higher for 0.2 mm reconstructions (3.8±0.8 vs 3.6±0.7). Of 335 coronary segments, none were classified as "unevaluable" while 87% vs. 76% were classified as "perfect" in 0.2 mm vs. 0.4 mm reconstructions (p < 0.001). Full confidence to rule-in or rule out significant coronary stenoses was achieved in 93% of segments in both reconstructions. The number of non-calcified plaques identified in 0.2 mm reconstructions was numerically higher than in 0.4 mm reconstructions (77 vs. 71, p = n.s.). On the Likert scale, the confidence to identify parameters of plaque vulnerability was significantly higher for 0.2 mm reconstructions (1.93 vs. 1.85, p < 0.001). In a selected patient group, photon counting CT coronary angiography demonstrated excellent image quality and an extremely low rate of unevaluable coronary segments. High-resolution reconstructions improve subjective image quality as was as the assessment of vulnerable plaque characteristics.

B-Lines in the Assessment of Interstitial Lung Disease Associated with Scleroderma: The Role of Handheld Devices.

Background: Timely detection and aggressive management of interstitial lung disease (ILD) in systemic sclerosis (SSc) are essential to improving outcomes and reducing risks of irreversible lung injury. Objective: to explore the usefulness of an ultraportable ultrasound device for the management of SSc-related ILD and to compare it with clinical and instrumental data. Methods: A total of 19 consecutive SSc patients underwent a comprehensive pulmonary evaluation: clinical, pulmonary function tests (PFTs) (spirometry, DLCO), lung CT (1.5 mm slice thickness reconstruction; HRCT), and lung ultrasound (LUS). A total score was calculated based on the number of color-coded B-lines recorded for each lung sliding. B-lines were analyzed against dyspnea, cough, Velcro, CT imaging (Warrick's score), and PFTs. Global and subgroup analysis were performed (diffuse versus limited cutaneous SSc, Warrick's < 7 versus >7). Results: Symptomatic lung involvement with varying degrees of dyspnea was reported in about 74% of cases (functional NYHA > 2 in more than half), chronic dry cough in one-third, Velcro rales in 42%. A total of 84.24% were classified as SSc with ILD on CT imaging. Statistically significant mild-to-moderate correlations between B-lines and clinical manifestations were demonstrated, as well as PFTs and Warrick's scores (more B-lines, lower pulmonary function, but higher extent and severity on CT) (p < 0.05); there were differences between SSc patients without and with ILD in terms of the number and distribution of B-lines (p < 0.05), as well as different B-lines patterns and numbers in diffuse versus limited SSc (p < 0.05). Conclusions: Ultraportable handheld LUS is a promising method suitable for the management (screening, early detection, and evaluation) of SSc patients.

Image quality assessments in abdominal CT: Relative importance of dose, iterative reconstruction strength and slice thickness

IntroductionLow contrast resolution in abdominal computed tomography (CT) may be negatively affected by attempts to lower patient doses. Iterative reconstruction (IR) algorithms play a key role in mitigating this problem. The reconstructed slice thickness also influences image quality. The aim was to assess the interaction and influence of patient dose, slice thickness, and IR strength on image quality in abdominal CT. MethodWith a simultaneous acquisition, images at 42 and 98 mAs were obtained in 25 patients. Multiplanar images with slice thicknesses of 1, 2, and 3 mm and advanced modeled iterative reconstruction (ADMIRE) strengths of 3 (AD3) and 5 (AD5) were reconstructed. Four radiologists evaluated the images in a pairwise manner based on five image criteria. Ordinal logistic regression with mixed effects was used to evaluate the effect of tube load, ADMIRE strength, and slice thickness using the visual grading regression technique. ResultsFor all assessed image criteria, the regression analysis showed significantly (p < 0.001) higher image quality for AD5, but lower for tube load 42 mAs, and slice thicknesses of 1 mm and 2 mm, compared to the reference categories of AD3, 98 mAs, and 3 mm, respectively. AD5 at 2 mm was superior to AD3 at 3 mm for all image criteria studied. AD5 1 mm produced inferior image quality for liver parenchyma and overall image quality compared to AD3 3 mm. Interobserver agreement (ICC) ranged from 0.874 to 0.920. ConclusionADMIRE 5 at 2 mm slice thickness may allow for further dose reductions due to its superiority when compared to ADMIRE 3 at 3 mm slice thickness. Implications for practiceCombination of thinner slices and higher ADMIRE strength facilitates imaging at low dose.

Relationship between pericoronary adipose tissue attenuation value and image reconstruction parameters

Rationale and objectivesTo investigate the relationship between the pericoronary adipose tissue CT mean attenuation (PCATMA) measurement and image reconstruction parameters (adaptive statistical iterative reconstruction-veo (ASIR-V) percentage, kernel, and slice thickness). Materials and methodsOne hundred and ninety-eight consecutive patients underwent CT coronary angiography at 100 kilovoltage peak (kVp) (n = 102) and 120 kVp (n = 96) were included. All scans were reconstructed by three means: 1. with 11 different ASIR-V percentages, standard kernel and 0.625 mm; 2. with soft, standard, detail, and bone kernels, 60 % ASIR-V, and 0.625 mm; 3. at 0.625 mm and 1.25 mm slice thickness, standard kernel and 60 % ASIR-V. PCATMA of the three main coronary arteries was calculated using a dedicated software. Linear regression, analysis of variance (ANOVA), Friedman test, and paired t-test were used for statistical analysis. ResultsLinear regression of pooled average data showed that the PCATMA was positively and linearly correlated with the ASIR-V percentage (all R squared >0.99). Regression analysis of individual data showed that most R squared were greater than 0.8 or 0.9, but their slope consisted of a relatively wide range. The difference of PCATMA among different kernels for each coronary artery reached statistically significant levels (P < 0.001), particularly for the difference between standard and bone kernel. Most of the differences between 0.625 mm and 1.25 mm for LAD, LCX, and RCA at 100 kVp and 120 kVp reached statistical significance (P < 0.001). ConclusionsPCATMA correlates linearly with the strength of ASIR-V. Reconstruction kernel and slice thickness also affect PCATMA, especially for the sharp kernels.

Assessing the impact of nodule features and software algorithm on pulmonary nodule measurement uncertainty for nodules sized 20 mm or less.

Measurements are not exact, so that if a measurement is repeated, one would get a different value each time. The spread of these values is the measurement uncertainty. Understanding measurement uncertainty of pulmonary nodules is important for proper interpretation of size and growth measurements. Larger amounts of measurement uncertainty may require longer follow-up intervals to be confident that any observed growth is due to actual growth rather than measurement uncertainty. We examined the influence of nodule features and software algorithm on measurement uncertainty of small, solid pulmonary nodules. Volumes of 107 nodules were measured on 4-6 repeated computed tomography (CT) scans (Siemens Somatom AS, 100 kVp, 120 mA, 1.0 mm slice thickness reconstruction) prospectively obtained during CT-guided fine needle aspiration biopsy between 2015-2021 at Department of Diagnostic, Molecular, and Interventional Radiology in Icahn School of Medicine at Mount Sinai, using two different automated volumetric algorithms. For each, the coefficient of variation (standard deviation divided by the mean) of nodule volume measurements was determined. The following features were considered: diameter, location, vessel and pleural attachments, nodule surface area, and extent of the nodule in the three acquisition dimensions of the scanner. Median volume of 107 nodules was 515.23 and 535.53 mm3 for algorithm #1 and #2, respectively with excellent agreement (intraclass correlation coefficient =0.98). Median coefficient of variation of nodule volume was low for the two algorithms, but significantly different (4.6% vs. 8.7%, P<0.001). Both algorithms had a trend of decreasing coefficient of variation of nodule volume with increasing nodule diameter, though only significant for algorithm #2. Coefficient of variation of nodule volume was significantly associated with nodule volume (P=0.02), attachment to blood vessels (P=0.02), and nodule surface area (P=0.001) for algorithm #2 using a multiple linear regression model. Correlation between the coefficient of variation (CoV) of nodule volume and the CoV of the x, y, z measurements for algorithm #1 were 0.29 (P=0.0021), 0.25 (P=0.009), and 0.80 (P<0.001) respectively, and for algorithm #2, 0.46 (P<0.001), 0.52 (P<0.001), and 0.58 (P<0.001), respectively. Even in the best-case scenario represented in this study, using the same measurement algorithm, scanner, and scanning protocol, considerable measurement uncertainty exists in nodule volume measurement for nodules sized 20 mm or less. We found that measurement uncertainty was affected by interactions between nodule volume, algorithm, and shape complexity.

Impact of reconstruction parameters on the accuracy of myocardial extracellular volume quantification on a first-generation, photon-counting detector CT

BackgroundThe potential role of cardiac computed tomography (CT) has increasingly been demonstrated for the assessment of diffuse myocardial fibrosis through the quantification of extracellular volume (ECV). Photon-counting detector (PCD)-CT technology may deliver more accurate ECV quantification compared to energy-integrating detector CT. We evaluated the impact of reconstruction settings on the accuracy of ECV quantification using PCD-CT, with magnetic resonance imaging (MRI)-based ECV as reference.MethodsIn this post hoc analysis, 27 patients (aged 53.1 ± 17.2 years (mean ± standard deviation); 14 women) underwent same-day cardiac PCD-CT and MRI. Late iodine CT scans were reconstructed with different quantum iterative reconstruction levels (QIR 1−4), slice thicknesses (0.4−8 mm), and virtual monoenergetic imaging levels (VMI, 40−90 keV); ECV was quantified for each reconstruction setting. Repeated measures ANOVA and t-test for pairwise comparisons, Bland–Altman plots, and Lin’s concordance correlation coefficient (CCC) were used.ResultsECV values did not differ significantly among QIR levels (p = 1.000). A significant difference was observed throughout different slice thicknesses, with 0.4 mm yielding the highest agreement with MRI-based ECV (CCC = 0.944); 45-keV VMI reconstructions showed the lowest mean bias (0.6, 95% confidence interval 0.1–1.4) compared to MRI. Using the most optimal reconstruction settings (QIR4. slice thickness 0.4 mm, VMI 45 keV), a 63% reduction in mean bias and a 6% increase in concordance with MRI-based ECV were achieved compared to standard settings (QIR3, slice thickness 1.5 mm; VMI 65 keV).ConclusionsThe selection of appropriate reconstruction parameters improved the agreement between PCD-CT and MRI-based ECV.Relevance statementTailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility.Key points• CT is increasingly promising for myocardial tissue characterization, assessing focal and diffuse fibrosis via late iodine enhancement and ECV quantification, respectively.• PCD-CT offers superior performance over conventional CT, potentially improving ECV quantification and its agreement with MRI-based ECV.• Tailoring PCD-CT reconstruction parameters optimizes ECV quantification compared to MRI, potentially improving its clinical utility.Graphical

Protocol selection formalism for minimizing detectable differences in morphological radiomics features of lung lesions in repeated CT acquisitions.

The accuracy of morphological radiomic features (MRFs) can be affected by various acquisition settings and imaging conditions. To ensure that clinically irrelevant changes do not reduce sensitivity to capture the radiomics changes between successive acquisitions, it is essential to determine the optimal imaging systems and protocols to use. The main goal of our study was to optimize CT protocols and minimize the minimum detectable difference (MDD) in successive acquisitions of MRFs. MDDs were derived based on the previous research involving 15 realizations of nodule models at two different sizes. Our study involved simulations of two consecutive acquisitions using 297 different imaging conditions, representing variations in scanners' reconstruction kernels, dose levels, and slice thicknesses. Parametric polynomial models were developed to establish correlations between imaging system characteristics, lesion size, and MDDs. Additionally, polynomial models were used to model the correlation of the imaging system parameters. Optimization problems were formulated for each MRF to minimize the approximated function. Feature importance was determined for each MRF through permutation feature analysis. The proposed method was compared to the recommended guidelines by the quantitative imaging biomarkers alliance (QIBA). The feature importance analysis showed that lesion size is the most influential parameter to estimate the MDDs in most of the MRFs. Our study revealed that thinner slices and higher doses had a measurable impact on reducing the MDDs. Higher spatial resolution and lower noise magnitude were identified as the most suitable or noninferior acquisition settings. Compared to QIBA, the proposed protocol selection guideline demonstrated a reduced coefficient of variation, with values decreasing from 1.49 to 1.11 for large lesions and from 1.68 to 1.12 for small lesions. The protocol optimization framework provides means to assess and optimize protocols to minimize the MDD to increase the sensitivity of the measurements in lung cancer screening.

Assessing variability in non-contrast CT for the evaluation of stroke: The effect of CT image reconstruction conditions on AI-based CAD measurements of ASPECTS value and hypodense volume.

To rule out hemorrhage, non-contrast CT (NCCT) scans are used for early evaluation of patients with suspected stroke. Recently, artificial intelligence tools have been developed to assist with determining eligibility for reperfusion therapies by automating measurement of the Alberta Stroke Program Early CT Score (ASPECTS), a 10-point scale with > 7 or ≤ 7 being a threshold for change in functional outcome prediction and higher chance of symptomatic hemorrhage, and hypodense volume. The purpose of this work was to investigate the effects of CT reconstruction kernel and slice thickness on ASPECTS and hypodense volume. The NCCT series image data of 87 patients imaged with a CT stroke protocol at our institution were reconstructed with 3 kernels (H10s-smooth, H40s-medium, H70h-sharp) and 2 slice thicknesses (1.5mm and 5mm) to create a reference condition (H40s/5mm) and 5 non-reference conditions. Each reconstruction for each patient was analyzed with the Brainomix e-Stroke software (Brainomix, Oxford, England) which yields an ASPECTS value and measure of total hypodense volume (mL). An ASPECTS value was returned for 74 of 87 cases in the reference condition (13 failures). ASPECTS in non-reference conditions changed from that measured in the reference condition for 59 cases, 7 of which changed above or below the clinical threshold of 7 for 3 non-reference conditions. ANOVA tests were performed to compare the differences in protocols, Dunnett's post-hoc tests were performed after ANOVA, and a significance level of p < 0.05 was defined. There was no significant effect of kernel (p = 0.91), a significant effect of slice thickness (p < 0.01) and no significant interaction between these factors (p = 0.91). Post-hoc tests indicated no significant difference between ASPECTS estimated in the reference and any non-reference conditions. There was a significant effect of kernel (p < 0.01) and slice thickness (p < 0.01) on hypodense volume, however there was no significant interaction between these factors (p = 0.79). Post-hoc tests indicated significantly different hypodense volume measurements for H10s/1.5mm (p = 0.03), H40s/1.5mm (p < 0.01), H70h/5mm (p < 0.01). No significant difference was found in hypodense volume measured in the H10s/5mm condition (p = 0.96). Automated ASPECTS and hypodense volume measurements can be significantly impacted by reconstruction kernel and slice thickness.

Development and Application of a Virtual Imaging Trial Framework for Longitudinal Quantification of Emphysema in CT.

Pulmonary emphysema is a progressive lung disease that requires accurate evaluation for optimal management. This task, possible using quantitative CT, is particularly challenging as scanner and patient attributes change over time, negatively impacting the CT-derived quantitative measures. Efforts to minimize such variations have been limited by the absence of ground truth in clinical data, thus necessitating reliance on clinical surrogates, which may not have one-to-one correspondence to CT-based findings. This study aimed to develop the first suite of human models with emphysema at multiple time points, enabling longitudinal assessment of disease progression with access to ground truth. A total of 14 virtual subjects were modeled across three time points. Each human model was virtually imaged using a validated imaging simulator (DukeSim), modeling an energy-integrating CT scanner. The models were scanned at two dose levels and reconstructed with two reconstruction kernels, slice thicknesses, and pixel sizes. The developed longitudinal models were further utilized to demonstrate utility in algorithm testing and development. Two previously developed image processing algorithms (CT-HARMONICA, EmphysemaSeg) were evaluated. The results demonstrated the efficacy of both algorithms in improving the accuracy and precision of longitudinal quantifications, from 6.1±6.3% to 1.1±1.1% and 1.6±2.2% across years 0-5. Further investigation in EmphysemaSeg identified that baseline emphysema severity, defined as >5% emphysema at year 0, contributed to its reduced performance. This finding highlights the value of virtual imaging trials in enhancing the explainability of algorithms. Overall, the developed longitudinal human models enabled ground-truth based assessment of image processing algorithms for lung quantifications.

Coronary artery calcium scoring assessment in ultra-low-dose chest computed tomography

ObjectivesTo investigate the effect of non-electrocardiogram (ECG) -triggered ultra-low-dose CT (ULD-CT) with different reconstruction protocols on coronary artery calcium (CAC) scoring assessment, compared with ECG-triggered CAC CT (CAC-CT). MethodsThis prospective study included 115 patients who underwent CAC-CT and ULD-CT scans under the same topogram images. CAC-CT adopted a prospective ECG-triggered sequential acquisition with a tube potential of 120 kV, and the reconstruction protocol was standard Qr36 + slice 3 mm (CACQr-3mm group). ULD-CT adopted a non-ECG-triggered high-pitch acquisition with a tube potential of Sn100 kV, and four groups of images (named ULDQr-3mm, ULDSa-3mm, ULDQr-1.5mm, and ULDSa-1.5mm) were reconstructed using different reconstruction algorithms (standard Qr36, kV-independent Sa36) and slice thicknesses (3 mm, 1.5 mm). The accuracy of CAC detection by ULD-CT was calculated. The agreement of the CAC score between ULD-CT and CAC-CT scans was assessed using intraclass correlation coefficients (ICC) and Bland-Altman plot, and the agreement of risk categorization was assessed using weighted kappa. ResultsThe sensitivity and specificity of the ULDSa-1.5mm group for detecting positive CAC were 100% and 97.4%, respectively (k = 0.980). The CAC score for the ULDSa-3mm and ULDSa-1.5mm groups demonstrated excellent agreement with the CACQr-3mm group (ICC = 0.992, 0.990, respectively), with a mean difference of −12.3 and − 12.4. The agreement of risk categorization based on absolute and percentile CAC score between the ULDSa-1.5mm and CACQr-3mm groups was excellent (weighted k = 0.954, 0.983, respectively), and risk reclassification rates were low (3.5%, 2.8%, respectively). The effective dose was reduced by approximately 77.2% for the ULD-CT compared to the CAC-CT (0.18 mSv vs. 0.79 mSv, p < 0.001). ConclusionReconstruction with a 1.5-mm slice thickness and kV-independent iterative algorithmic protocol in ULD-CT yielded excellent agreement in CAC score quantification and risk categorization compared with ECG-triggered CAC-CT.

The diagnosis performance of convolutional neural network in the detection of pulmonary nodules: a systematic review and meta-analysis.

Pulmonary nodules are an early imaging indication of lung cancer, and early detection of pulmonary nodules can improve the prognosis of lung cancer. As one of the applications of machine learning, the convolutional neural network (CNN) applied to computed tomography (CT) imaging data improves the accuracy of diagnosis, but the results could be more consistent. To evaluate the diagnostic performance of CNN in assisting in detecting pulmonary nodules in CT images. PubMed, Cochrane Library, Web of Science, Elsevier, CNKI and Wanfang databases were systematically retrieved before 30 April 2023. Two reviewers searched and checked the full text of articles that might meet the criteria. The reference criteria are joint diagnoses by experienced physicians. The pooled sensitivity, specificity and the area under the summary receiver operating characteristic curve (AUC) were calculated by a random-effects model. Meta-regression analysis was performed to explore potential sources of heterogeneity. Twenty-six studies were included in this meta-analysis, involving 2,391,702 regions of interest, comprising segmented images with a few wide pixels. The combined sensitivity and specificity values of the CNN model in detecting pulmonary nodules were 0.93 and 0.95, respectively. The pooled diagnostic odds ratio was 291. The AUC was 0.98. There was heterogeneity in sensitivity and specificity among the studies. The results suggested that data sources, pretreatment methods, reconstruction slice thickness, population source and locality might contribute to the heterogeneity of these eligible studies. The CNN model can be a valuable diagnostic tool with high accuracy in detecting pulmonary nodules.

MSCT Thoracolumbal Kontras pada Suspek Metastasis Tulang Belakang: Studi Kasus di Rumah Sakit Hermina Pandanaran Semarang

Background: MSCT is a routine imaging modality for detecting bone metastases. The use of 1.25 mm slice thickness reconstruction on Thoracolumbar MSCT examination at Hermina Pandanaran Hospital is different from preliminary studies. This study aims to determine MSCT Thoracolumbar contrast with 1.25 mm slice thickness and 3D reconstruction to produce information on anatomical images in suspected cases of spinal metastases. Methods: This research was qualitative with a case study approach. The respondents were 3 radiographers, 2 radiologists, and 1 referring doctor. Data collection by observation, interviews, and document studies. Processing and data analysis used open coding and analysis to obtain conclusions. Results: The examination procedure was carried out by preparing the patient to fast for 6 hours before the examination, checking the results of ureum creatinine, filling out the informed consent and doing a skin test. Contrast media as much as 1.1-1.2 ml/kg per patient's body weight plus saline half of the amount of contrast, flow rate 2.5-3 mL/s, scan delay 25 s. DFOV 25-35cm, ASIR 40%. Reconstruction of slice thickness 1.25 mm to get more detailed results so that it could produce informative images that evaluated the spine and soft tissue. MPR and 3D reconstruction so that the image looked real bone and could be viewed 360ᵒ. Conclusions: The resulting slice thickness of 1.25mm and 3D reconstruction produced anatomical image information that could visualize bone to see destructive lytic lesions due to metastases, and visualize soft tissue such as paravertebral masses or discs.

Quantitative analysis of small coronary artery calcium detectability with an accurate simulation and validation on a clinical CT scanner.

The absence of coronary artery calcium (CAC) measured via CT is associated with very favorable prognosis, and current guidelines recommend low-density lipoprotein cholesterol (LDL-c) lowering therapy for individuals with any CAC. This motivates early detection of small granules of CAC; however, calcium scan sensitivity for detecting very low levels of calcium has not been quantified. In this work, the size limit of detectability of small calcium hydroxyapatite (CaHA) granules with clinical CAC scanning was assessed using validated simulations. CT projections of digital 3D mathematical phantoms containing small CaHA granules were simulated analytically; images were reconstructed using a filter designed to reproduce the point spread function of a specific commercial scanner, and a relationship of HU number versus diameter was derived. These simulation results were validated with experimental measurements of HU versus diameter from phantoms containing small granules of CaHA on a GE Revolution CT scanner in the clinic; ground truth measurements of the CaHA granule diameters were obtained using a Zeiss Xradia 510 Versa high-resolution 3D micro-CT imaging system. Using experimental measurements on the clinical CT scanner, detectability was quantified with a detectability index (d') using a non-prewhitened matched filter. The effect of changes to reconstruction slice thickness and reconstruction kernel on granule detectability was evaluated. Under typical clinical calcium scanning and reconstruction conditions, the minimum detectable diameter of a simulated spherical calcium granule with a clinically relevant CaHA density was 0.76mm. The minimum detectable volume was 2.4 times smaller on images reconstructed at a slice thickness of 0.625mm compared to 2.5mm. The detectability index d' increased by a factor of 1.7 when images were reconstructed with 0.625mm slices compared to 2.5mm slices. d' did not change when images were reconstructed with the high-resolution BONE filter compared to the less sharp STANDARD resolution filter on the GE Revolution CT. We have quantified detectability versus size of small calcium granules at the resolution limit of a widely available clinical CT scanner. Detectability increased significantly with reduced slice thickness and did not change with a sharper reconstruction kernel. The simulation can be used to calculate the trade-off between dose and CAC detectability.

Ultrahigh-Resolution Photon-Counting Detector CT of the Lungs: Association of Reconstruction Kernel and Slice Thickness With Image Quality.

BACKGROUND. Prior work has shown improved image quality for photon-counting detector (PCD) CT of the lungs compared with energy-integrating detector CT. A paucity of the literature has compared PCD CT of the lungs using different reconstruction parameters. OBJECTIVE. The purpose of this study is to the compare the image quality of ultra-high-resolution (UHR) PCD CT image sets of the lungs that were reconstructed using different kernels and slice thicknesses. METHODS. This retrospective study included 29 patients (17 women and 12 men; median age, 56 years) who underwent noncontrast chest CT from February 15, 2022, to March 15, 2022, by use of a commercially available PCD CT scanner. All acquisitions used UHR mode (1024 × 1024 matrix). Nine image sets were reconstructed for all combinations of three sharp kernels (BI56, BI60, and BI64) and three slice thicknesses (0.2, 0.4, and 1.0 mm). Three radiologists independently reviewed reconstructions for measures of visualization of pulmonary anatomic structures and pathologies; reader assessments were pooled. Reconstructions were compared with the clinical reference reconstruction (obtained using the BI64 kernel and a 1.0-mm slice thickness [BI641.0-mm]). RESULTS. The median difference in the number of bronchial divisions identified versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.5), BI600.4-mm (0.3), BI640.2-mm (0.5), and BI600.2-mm (0.2) (all p < .05). The median bronchial wall sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3) and BI640.2-mm (0.3) and was lower for BI561.0-mm (-0.7) and BI560.4-mm (-0.3) (all p < .05). Median pulmonary fissure sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3), BI600.4-mm (0.3), BI560.4-mm (0.5), BI640.2-mm (0.5), BI600.2-mm (0.5), and BI560.2-mm (0.3) (all p < .05). Median pulmonary vessel sharpness versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3), BI600.4-mm (-0.3), BI560.4-mm (-0.7), BI640.2-mm (-0.7), BI600.2-mm (-0.7), and BI560.2-mm (-0.7). Median lung nodule conspicuity versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3) and BI560.4-mm (-0.3) (both p < .05). Median conspicuity of all other pathologies versus the clinical reference reconstruction was lower for reconstructions with BI561.0 mm (-0.3), BI560.4-mm (-0.3), BI640.2-mm (-0.3), BI600.2-mm (-0.3), and BI560.2-mm (-0.3). Other comparisons among reconstructions were not significant (all p > .05). CONCLUSION. Only the reconstruction using BI640.4-mm yielded improved bronchial division identification and bronchial wall and pulmonary fissure sharpness without a loss in pulmonary vessel sharpness or conspicuity of nodules or other pathologies. CLINICAL IMPACT. The findings of this study may guide protocol optimization for UHR PCD CT of the lungs.

Computed tomography-based measurements of normative liver and spleen volumes in children.

Quantification of organ size has utility in clinical care and research for diagnostics, prognostics and surgical planning. Volumetry is regarded as the best measure of organ size and change in size over time. Scarce reference values exist for liver and spleen volumes in healthy children. To report liver and spleen volumes for a sample of children defined by manual segmentation of contrast-enhanced CT images with the goal of defining normal values and thresholds that might indicate disease. This retrospective study included clinically acquired contrast-enhanced CTs of the abdomen/pelvis for children and adolescents imaged between January 2018 and July 2021. Liver and spleen volumes were derived through manual segmentation of CTs reconstructed at 2.5-, 3- or 5-mm slice thickness. A subset of images (5%, n=16) was also segmented using 0.5-mm slice thickness reconstructions to define agreement based on image slice thickness. We used Pearson correlation and multivariable regression to assess associations between organ volumes and patient characteristics. We generated reference intervals for the 5th, 25th, 50th (median), 75th and 95th percentiles for organ volumes as a function of age and weight using quantile regression models. Finally, we calculated Bland-Altman plots and intraclass correlation coefficients (ICC) to quantify agreement. We included a total of 320 children (mean age ± standard deviation [SD] = 9±4.6years; mean weight 38.1±18.8kg; 160 female). Liver volume ranged from340-2,002mL, and spleen volume ranged from 28-480mL. Patient weight (kg) (β=12.5), age (months) (β=1.7) and sex (female) (β = -35.3) were independent predictors of liver volume, whereas patient weight (kg) (β=2.4) and age (months) (β=0.3) were independent predictors of spleen volume. There was excellent absolute agreement (ICC=0.99) and minimal absolute difference (4mL) in organ volumes based on reconstructed slice thickness. We report reference liver and spleen volumes for children without liver or spleen disease. These results provide reference ranges and potential thresholds to identify liver and spleen size abnormalities that might reflect disease in children.

Optimization of Ct-Spn Anatomical Image of Coronal Section With Slice Thickness Reconstruction Variations and Increment Reconstruction in Rhinosinusitis Cases Chronic at Rs Balimed

Background: One of the modalities used to diagnose rhinosinusitis is CT Scan. In CT Scan, there are several parameters, namely slice thickness and reconstruction increment. Objective: aims to determine the optimization of the CT-SPN anatomical image produced with variations in slice thickness and reconstruction Methods: This type of research is a quantitative study with an experimental approach conducted at Balimed Hospital from July to August 2022. Results: Friedman test results for the whole anatomy showed a significance p of 0.0001 (p value &lt;0.05) which means Ho is rejected and Ha is accepted which means that there is a significant difference in the anatomical image information of CT Scan of the paranasal sinuses in coronal sections with variations in slice thickness reconstruction and incremental reconstruction in chronic rhinosinusitis. And based on the Wilcoxon test, it also showed that each variation had a p value &lt;0.05, which means that there are differences in anatomical image information for each variation. Conslusion: The conclusion of this study, based on this study, shows that there are differences in information on the coronal CT-SPN anatomical image with variations in slice thickness and increment reconstruction in cases of chronic rhinosinusitis and variation 2 has the most optimal anatomical image information. Based on the Wilcoxon test, it also shows that each variation has different anatomical image information.

A comprehensive quality assurance procedure for 4D CT commissioning and periodic QA.

The 4D computed tomography (CT) simulation is an essential procedure for tumors exhibiting breathing-induced motion. However, to date there are no established guidelines to assess the characteristics of existing systems and to describe meaningful performance. We propose a commissioning quality assurance (QA) protocol consisting of measurements and acquisitions that assess the mechanical and computational operation for 4D CT with both phase and amplitude-based reconstructions, for regular and irregular respiratory patterns. The 4D CT scans of a QUASAR motion phantom were acquired for both regular and irregular breathing patterns. The hardware consisted of the Canon Aquilion Exceed LB CT scanner used in conjunction with the Anzai laser motion monitoring system. The nominal machine performance and reconstruction were demonstrated with measurements using regular breathing patterns. For irregular breathing patterns the performance was quantified through the analysis of the target motion in the superior and inferior directions, and the volume of the internal target volume (ITV). Acquisitions were performed using multiple pitches and the reconstructions were performed using both phase and amplitude-based binning. The target was accurately captured during regular breathing. For the irregular breathing, the measured ITV exceeded the nominal ITV parameters in all scenarios, but all deviations were less than the reconstructed slice thickness. The mismatch between the nominal pitch and the actual breathing rate did not affect markedly the size of the ITV. Phase and normalized amplitude binning performed similarly. We demonstrated a framework for measuring and quantifying the initial performance of 4D CT simulation scans that can also be applied during periodic QAs. The regular breathing provided confidence that the hardware and the software between the systems performs adequately. The irregular breathing data suggest that the system may be expected to capture in excess the target motion and geometry, but the deviation is expected to be within the slice thickness.

Thrombus Density in Acute Basilar Artery Occlusion Depends on Slice Thickness and the Method of Manual Thrombus Delineation.

Introduction: High thrombus attenuation on CT has been suggested as a predictor of successful recanalization. It is as well speculated that thrombi of different density may be susceptible to different methods of mechanical thrombectomy. In this study we sought to determine the effect of different methods of manual thrombus delineation and reconstructed slice thickness on thrombus density. Material and Methods: Fifty-six patients with acute occlusion of the basilar artery treated with endovascular therapy were retrospectively included. Clinical, demographic, radiological and outcome parameters were collected. Two raters measured absolute and relative thrombus density employing three different methods (one region of interest, three regions of interest, whole thrombus delineation) and using three different reconstructed slice thicknesses (0.625, 2.5 and 5 mm) of the original admission CT. Results: Thirty-nine patients were successfully recanalized (thrombolysis in cerebral infarction score ≥ 2b). Good clinical outcome (modified Rankin scale ≤ 2) occurred significantly more often in the recanalized group (36 vs. 6%, p = 0.023, Fisher’s exact test), in the non-recanalized group symptomatic intracranial hemorrhage occurred more often (9 vs. 29%, p = 0.001, Fisher’s exact test). Absolute and relative thrombus density were largely different between methods and slice thicknesses. Multiple regression showed a decrease of thrombus density with increasing slice thickness (β = −3.98, p < 0.001) and logistic regression showed a statistically significant but very small relation between density and recanalization (β = 0.006, odds ratio (95% confidence interval) = 1.006 (1.003–1.01), p < 0.001). Conclusions: The methods for manual thrombus delineation and reconstructed slice thickness had a significant influence on absolute and relative thrombus density. Density alone may be of limited value as a predictive marker for recanalization success in acute occlusion of the basilar artery. Standards for density measurements must be defined when comparing different studies and when evaluating different methods of mechanical thrombectomy.

Different CT slice thickness and contrast-enhancement phase in radiomics models on the differential performance of lung adenocarcinoma.

BackgroundTo investigate the effects of computed tomography (CT) reconstruction slice thickness and contrast‐enhancement phase on the differential diagnosis performance of radiomic signature in lung adenocarcinoma.MethodsA total of 187 patients who had been pathologically confirmed with lung adenocarcinoma and nonadenocarcinoma were divided into a training cohort (n = 149) and validation cohort (n = 38). All the patients underwent contrast‐enhanced CT and the images were reconstructed with different slice thickness. The radiomic features were extracted from different slice thickness and scan phase. The logistic regression (LR) algorithm was used to build a machine learning model for each group. The area under the curve (AUC) obtained from the receiver operating characteristic (ROC) curve and DeLong test was used to evaluate its discriminating performance.ResultsFinally, 34 image features and five semantic features were selected to establish a radiomics model. Based on the three contrast‐enhanced CT phases and four reconstruction slice thickness, 12 groups of radiomics models showed good discrimination ability with the AUCs range from 0.9287 to 0.9631, sensitivity range from 0.8349 to 0.9083, specificity range from 0.825 to 0.925 in the training group. Similar results were observed in the validation group. However, there was no statistical significance between the different CT scan phase groups and different slice thickness (p > 0.05).ConclusionsThe radiomic analysis of contrast‐enhanced CT can be used for the differential diagnosis of lung adenocarcinoma. Moreover, different slice thickness and contrast‐enhanced scan phase did not affect the discriminating ability in the radiomics models.

Accelerated Three-dimensional T2-Weighted Turbo-Spin-Echo Sequences with Inner-Volume Excitation and Iterative Denoising in the Setting of Pelvis MRI at 1.5T: Impact on Image Quality and Lesion Detection

To investigate image quality and rate of lesion detection in a novel three-dimensional T2-weighted turbo-spin-echo sequence with inner-volume excitation (zoomed imaging) and iterative denoising processing in pelvic MRI at 1.5T. Two-dimensional T2-weighted turbo-spin-echo sequences were used as the clinical reference standard (2D-T2-TSE). This is a prospective study of patients with various pelvic pathologies. Each patient underwent standard 2D-T2-TSE in three planes with two-fold acceleration as well as a single three-dimensional T2-TSE in the sagittal plane with four-fold acceleration known as Sampling-Perfection-with-Application-optimized-Contrast-using-different-flip-angle-Evolutions (3D-T2-SPACE). The 3D-T2-SPACE images were reconstructed in three orthogonal planes at a slice thickness of 2 mm (vs. 2D-T2-TSE at 4 mm). Two radiologists conducted a qualitative image analysis on standard 2D-T2-TSE and multiplanar reconstructed 3D-T2-SPACE images. These parameters were compared and inter-reader agreement was computed. Furthermore, each reader documented the observed lesions of various pelvic organs. The rate of lesion detection was compared between readers and sequences. Inter-reader and inter-sequence agreement were computed. Forty patients (25 females) were included. Mean patient age was 58 ± 13 years. 3D-T2-SPACE enabled an approximate 22% reduction of acquisition time and 50% of reconstructed slice thickness. 3D-T2-SPACE showed fewer artifacts than 2D-T2-TSE (p < 0.001). However, 2D-T2-TSE was rated to have significantly higher signal intensity than 3D-T2-SPACE (p < 0.001). There were no significant differences between the two sequences regarding all other parameters. Inter-reader agreement regarding image quality parameters was substantial (Kappa=0.772). For all analyzed pelvic anatomic structures, inter-reader and inter-sequence agreement for lesion detection was excellent (Kappa > 0.80). 3D-T2-SPACE with the inner-volume excitation and iterative denoising is clinically feasible at 1.5 T, enabling faster imaging, thinner slices, and significant reduction of artifacts. Despite that signal intensity was inferior in the SPACE images, overall image quality, diagnostic confidence and lesion detection were not compromised. This prospective study sets the stage for further clinical implementation and future investigations tailored to specific indications in pelvis MRI.