CT Acquisition Protocol Research Articles

Optimizing CT Scan Parameters for Dry Archaeological Bones: A Qualitative Study as a First Step Towards Standardizing CT Acquisition Protocols

ABSTRACTEven though the use of CT scan examinations is often required in paleopathology, the method for performing a CT scan on archaeological dry bones has received little attention. Eight different CT acquisition parameters and positions on the CT table were evaluated using five healthy tibiae (including three immature bones), four healthy vertebrae (including three immature bones), and four pathological mature bones, all in a good state of preservation. The images obtained were blindly evaluated in a psychophysical and subjective manner by four evaluators with varying levels of experience in radiology. The evaluators preferred a tube voltage of 100 kV or less, or expressed no preference, in 90.4% of cases (p < 0.001). For tube current, no preference was noted in 57.7% of cases (p < 0.001), but when a preference was given, a value between 100 and 200 mAs was chosen in 95.5% of cases. The thinnest slices and centered positioning within the gantry, both vertically and laterally, were favored in 100% of cases (p < 0.001). There was no preference for the size of the field of view in 42.3% of cases. The positioning of the bone in the headrest was preferred in 71.2% of cases (p < 0.001), particularly for immature bones. Preferences regarding the elevation of the bone using a cardboard box were not significant (p = 0.07). We therefore recommend using a tube voltage of 80 kV, a tube current between 100 and 200 mAs, the thinnest possible slice thickness, and a field of view minimized according to the CT scanner's capabilities. Bones should be positioned in the headrest, perfectly centered both vertically and laterally within the gantry. However, these conclusions are based on a limited number of bones and types of bones, all in a good state of preservation, highlighting the need for further research.

Editorial Comment: Standardization of Cardiac CT Acquisition, Contrast Media, and Reconstruction Protocols Will Help Improve the Accuracy of PCAT Measurement.

Editorial Comment: Standardization of Cardiac CT Acquisition, Contrast Media, and Reconstruction Protocols Will Help Improve the Accuracy of PCAT Measurement.

Interscan reproducibility of computed tomography derived coronary plaque volume measurements using a semi-automated analysis software

Abstract Background Coronary computed tomography angiography (CCTA) enables detailed quantification and characterization of coronary atherosclerotic plaque, offering diagnostic and prognostic value. Despite the growing demand for accurate plaque analysis, studies on interscan reproducibility of automated plaque quantification are limited in number and size. Moreover, impact of clinical and technical factors on the reproducibility of plaque assessment tools are scarce. Purpose The objective of this study was to assess the interscan reproducibility of CCTA-derived plaque volume measurements and the implications of clinical and technical characteristics on interscan reproducibility. Methods A total of 101 patients with known coronary artery disease underwent two CCTA scans within hour interval using identical CT acquisition protocol. Coronary plaque volume measurements were quantified on a per-patient level using a contemporary semi-automated plaque analysis software. Results There was no statistically significant difference in median plaque volumes between the first and second scan. The direct correlation was excellent for volumes of non-calcified plaque (NCP), calcified plaque (CP), and total plaque (TP) across all analyses (Pearson’s coefficient 0.96 to 0.99), while moderate for low-density non-calcified plaque (LD-NCP) volumes (Pearson’s coefficient 0.77). Bland Altman analyses demonstrated high interscan agreement with narrow absolute and relative limits of agreement (LoA) across plaque subtypes, except for LD-NCP volumes (Table 1). Interscan reproducibility on CP volumes was affected by CT image quality with narrower LoA in scans with the highest image quality score (p = 0.003), or lowest image reconstructive iteration level (p <0.001). Limits of agreement were significantly narrower for NCP, CP, and TP volumes in lesions located in LAD compared to non-LAD lesions (p <0.001). However, no significant difference in LoA was present when comparing patients according to BMI (<27 and ≥27 kg/m2), heart rate (<65 and ≥65 beats per minute), or Agatston score (<193 and ≥193). Conclusions This comprehensive interscan reproducibility study revealed good agreement in the measurement of plaque subtypes. Adding new insight to existing literature, we have demonstrated that factors such as image quality, image reconstructive algorithms, and lesion location affect the reproducibility of plaque volume measurements. CT-derived plaque quantification using a semi-automated plaque analysis software holds potential for monitoring disease progression or regression in patients with CAD, provided high CCTA image quality.

A reference framework for standardization and harmonization of CT radiomics features on cadaveric sample

Radiomics features (RFs) serve as quantitative metrics to characterize shape, density/intensity, and texture patterns in radiological images. Despite their promise, RFs exhibit reproducibility challenges across acquisition settings, thus limiting implementation into clinical practice. In this investigation, we evaluate the effects of different CT scanners and CT acquisition protocols (KV, mA, field-of-view, and reconstruction kernel settings) on RFs extracted from lumbar vertebrae of a cadaveric trunk. Employing univariate and multivariate Generalized Linear Models (GLM), we evaluated the impact of each acquisition parameter on RFs. Our findings indicate that variations in mA had negligible effects on RFs, while alterations in kV resulted in exponential changes in several RFs, notably First Order (94.4%), GLCM (87.5%), and NGTDM (100%). Moreover, we demonstrated that a tailored GLM model was superior to the ComBat algorithm in harmonizing CT images. GLM achieved R2 > 0.90 in 21 RFs (19.6%), contrasting ComBat's mean R2 above 0.90 in only 1 RF (0.9%). This pioneering study unveils the effects of CT acquisition parameters on bone RFs in cadaveric specimens, highlighting significant variations across parameters and scanner datasets. The proposed GLM model presents a robust solution for mitigating these differences, potentially advancing harmonization efforts in Radiomics-based studies across diverse CT protocols and vendors.

Dose assessment in petrous bone CT: Effect of tube current modulation and scan length

The aim of this study is to compare the dosimetric performance of two CT acquisition protocols for the petrous bone: a standard fixed mAs protocol and a protocol using tube current modulation (TCM). By analyzing the scan length, dose-length product (DLP) and effective dose (ED) obtained with each protocol, we investigate whether TCM offers an advantage in terms of dose reduction while maintaining comparable image quality. To this end, 249 patients (women: 52%; men: 48%) were included in this study. The first center used TCM (120 kVp, 150 mA reference) for image acquisition, while the other centers opted for fixed mAs values. Acceptability of image quality was assessed using a standardized phantom (model 610 AAPM) by measuring noise uniformity and accuracy, contrast-to-noise ratio (CNR) and spatial resolution. The CTDIvol was not significantly different between center A and the other centers (p > 0.05), while DLP and ED were significantly different (p < 0.001), being reduced by a factor of 2 and 2.23 for scan length. We concluded that a scan with a 14.28% decrease in tube voltage from 140 kVp (136–170–210) mAs fixed to 120 kVp with TCM to 150 mA reference in helical scan mode can be recommended as an optimized protocol during CT examination of petrous bone while reducing DLP and ED to 50% without loss of diagnostic accuracy.

Split-bolus single-phase versus single-bolus split-phase CT acquisition protocols for staging in patients with testicular cancer: A retrospective study

IntroductionComputed tomography (CT) imaging has become indispensable in the management of medical oncology patients. Risks associated with high cumulative effective dose (CED) are relevant in testicular cancer patients. Split-bolus protocols, whereby the contrast medium injection is divided into two, followed by combining the required phase images in a single scan acquisition has been shown to provide images of comparable image quality and less radiation dose compared to single-bolus split-phase CT for various indications. We retrospectively evaluated the performance of split-bolus and single-bolus protocols in patients having follow-up CT imaging for testicular cancer surveillance. Methods45 patients with testicular cancer undergoing surveillance CT imaging of the thorax, abdomen, and pelvis who underwent split-bolus and single-bolus protocols were included. Quantitative image quality analysis was conducted by placing region of interests in pre-defined anatomical sub-structures within the abdominal cavity. The signal-to-noise ratio (SNR) and radiation dose in the form of dose length product (DLP) and effective dose (ED) were recorded. ResultsThe DLP and ED for the single-bolus, split-phase acquisition was 506 ± 89 mGy cm and 7.59 ± 1.3 mSv, respectively. For the split-bolus, single-phase acquisition, 397 ± 94 mGy∗cm and 5.95 ± 1.4 mSv, respectively (p < 0.000). This represented a 21.5 % reduction in radiation dose exposure. The SNR for liver, muscle and fat for the single-bolus were 7.4, 4.7 and 8, respectively, compared to 5.5, 3.8 and 7.4 in the split-bolus protocol (p < 0.001). ConclusionIn a testicular cancer patient cohort undergoing surveillance CT imaging, utilization of a split-bolus single-phase acquisition CT protocol enabled a significant reduction in radiation dose whilst maintaining subjective diagnostic acceptability.Implications for Practice: Use of split-bolus, single-phase acquisition has the potential to reduce CED in surveillance of testicular cancer patients.

The use of dynamic CT imaging for tracking mandibular movements in a phantom

Purpose. The objective of this study was to analyse the possibilities of using 4D CT scanning for the tracking of patients’ mandibles. Methods. A clinical 256-slice Revolution CT was used in obtaining 4D CT scans without table movement, with a novel mandibular phantom, mounted on a programmable six degrees-of-freedom Stewart Platform in motion. The phantom was used to simulate mandibular motions which are combinations of rotations with translations (depression, elevation, protrusion, retrusion and laterotrusion). The phantom was scanned five times during identical motion patterns with a dynamic CT acquisition protocol. An image processing workflow consisting of a pairwise rigid registration and semi-automatic segmentation was developed to extract kinematic parameters (cardan angles and point-of-interest displacements) from the dynamic sequences. Reproducibility was investigated by the 95% confidence interval and the absorbed organ dose to organs of interest in the primary beam were also estimated and compared to those of a standard CT scan of the brain Results. The maximum average 95% confidence interval for the displacement across all time points for the five repetitions was 0.61 mm (Y axis). In terms of rotations, the maximum average 95% confidence interval across all time points for the five repetitions was 1.39° (X axis). The effective dose for the dynamic scan was found to be 1.3 mSv, for a CTDIvol of 63.95 mGy and a DLP of 1023.14 mGycm. The absorbed organ doses were similar to organ doses during a clinical head CT scan. Conclusions. A framework is proposed to use 4D CT scanning as a possible methodology to evaluate the motion of the temporomandibular joint. The scanning protocol allows to visualise the motion by applying a semi-automated segmentation and registration. A graphical representation of all displacements in the three spatial dimensions can depict multiple points-of-interest at once during the same acquisition. A novel type of phantom was also introduced which simulates mandibular movement with six degrees-of-freedom (three translations and three rotations).

Evaluation of CT Acquisition Protocols Effect on Hounsfield Units and Optimization of CT-RED Calibration Curve Selection in Radiotherapy Treatment Planning Systems

Evaluation of CT Acquisition Protocols Effect on Hounsfield Units and Optimization of CT-RED Calibration Curve Selection in Radiotherapy Treatment Planning Systems

Individualized and Generalized Learner Models for Predicting Missed Hepatic Metastases.

The diagnostic performance of radiologist readers exhibits substantial variation that cannot be explained by CT acquisition protocol differences. Studying reader detectability from CT images may help identify why certain types of lesions are missed by multiple or specific readers. Ten subspecialized abdominal radiologists marked all suspected metastases in a multi-reader-multi-case study of 102 deidentified contrast-enhanced CT liver scans at multiple radiation dose levels. A reference reader marked ground truth metastatic and benign lesions with the aid of histopathology or tumor progression on later scans. Multi-slice image patches and 3D radiomic features were extracted from the CT images. We trained deep convolutional neural networks (CNN) to predict whether an average (generalized) or individual radiologist reader would detect or miss a specific metastasis from an image patch containing it. The individualized CNN showed higher performance with an area under the receiver operating characteristic curve (AUC) of 0.82 compared to a generalized one (AUC = 0.78) in predicting reader-specific detectability. Random forests were used to build the respective versions from radiomic features. Both the individualized (AUC = 0.64) and generalized (AUC = 0.59) predictors from radiomic features showed limited ability to differentiate detected from missed lesions. This shows that CNN can identify and learn automated features that are better predictors of reader detectability of lesions than radiomic features. Individualized prediction of difficult lesions may allow targeted training of idiosyncratic weaknesses but requires substantial training data for each reader.

The Feasibility of Low-dose Chest CT Acquisition Protocol for the Imaging of COVID-19 Pneumonia.

This study aimed to investigate the feasibility of low-dose chest CT acquisition protocol for the imaging of COVID 19 disease or suspects of this disease in adults. In this retrospective case-control study, the study group consisted of 141 patients who were imaged with low dose chest CT acquisition protocol. The control group consisted of 92 patients who were imaged with standard protocol. Anteroposterior and lateral diameters of chest, effective diameter and scan length, qualitative and quantitative noise levels, volumetric CT dose index (CTDIvol), dose length product (DLP), and size-specific dose estimations were compared between groups. Radiation dose reduction by nearly 90% (CTDIvol and DLP values 1.06 mGy and 40.3 mGy.cm vs. 8.07 mGy and 330 mGy.cm, respectively; p < 0.001) was achieved with the use of low-dose acquisition chest CT protocol. Despite higher image noise with low-dose acquisition protocol, no significant effect on diagnostic confidence was encountered. Cardiac and diaphragm movement-related artifacts were similar in both groups (p=0.275). Interobserver agreement was very good in terms of diagnostic confidence assessment. For the imaging of COVID-19 pneumonia or suspects of this disease in adults, lowdose chest CT acquisition protocol provides remarkable radiation dose reduction without adversely affecting image quality and diagnostic confidence.

Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

ObjectiveTo identify CT-acquisition parameters accounting for radiomics variability and to develop a post-acquisition CT-image correction method to reduce variability and improve radiomics classification in both phantom and clinical applications.MethodsCT-acquisition protocols were prospectively tested in a phantom. The multi-centric retrospective clinical study included CT scans of patients with colorectal/renal cancer liver metastases. Ninety-three radiomics features of first order and texture were extracted. Intraclass correlation coefficients (ICCs) between CT-acquisition protocols were evaluated to define sources of variability. Voxel size, ComBat, and singular value decomposition (SVD) compensation methods were explored for reducing the radiomics variability. The number of robust features was compared before and after correction using two-proportion z test. The radiomics classification accuracy (K-means purity) was assessed before and after ComBat- and SVD-based correction.ResultsFifty-three acquisition protocols in 13 tissue densities were analyzed. Ninety-seven liver metastases from 43 patients with CT from two vendors were included. Pixel size, reconstruction slice spacing, convolution kernel, and acquisition slice thickness are relevant sources of radiomics variability with a percentage of robust features lower than 80%. Resampling to isometric voxels increased the number of robust features when images were acquired with different pixel sizes (p < 0.05). SVD-based for thickness correction and ComBat correction for thickness and combined thickness–kernel increased the number of reproducible features (p < 0.05). ComBat showed the highest improvement of radiomics-based classification in both the phantom and clinical applications (K-means purity 65.98 vs 73.20).ConclusionCT-image post-acquisition processing and radiomics normalization by means of batch effect correction allow for standardization of large-scale data analysis and improve the classification accuracy.Key Points• The voxel size (accounting for the pixel size and slice spacing), slice thickness, and convolution kernel are relevant sources of CT-radiomics variability.• Voxel size resampling increased the mean percentage of robust CT-radiomics features from 59.50 to 89.25% when comparing CT scans acquired with different pixel sizes and from 71.62 to 82.58% when the scans were acquired with different slice spacings.• ComBat batch effect correction reduced the CT-radiomics variability secondary to the slice thickness and convolution kernel, improving the capacity of CT-radiomics to differentiate tissues (in the phantom application) and the primary tumor type from liver metastases (in the clinical application).

Patient-based low dose cone beam CT acquisition settings for prostate image-guided radiotherapy treatments on a Varian TrueBeam linear accelerator.

To evaluate the performance of low dose cone beam CT (CBCT) acquisition protocols for image-guided radiotherapy of prostate cancer. CBCT images of patients undergoing prostate cancer radiotherapy were acquired with the settings currently used in our department and two low dose settings at 50% and 63% lower exposure. Four experienced radiation oncologists and two radiation therapy technologists graded the images on five image quality characteristics. The scores were analysed through Visual Grading Regression, using the acquisition settings and the patient size as covariates. The low dose acquisition settings have no impact on the image quality for patients with body profile length at hip level below 100 cm. A reduction of about 60% of the dose is feasible for patients with size below 100 cm. The visibility of low contrast features can be compromised if using the low dose acquisition settings for patients with hip size above 100 cm. Low dose CBCT acquisition protocols for the pelvis, based on subjective evaluation of patient images.

Spectral Photon-Counting Computed Tomography (SPCCT): in-vivo single-acquisition multi-phase liver imaging with a dual contrast agent protocol

Diagnostic imaging of hepatocellular carcinoma (HCC) requires a liver CT or MRI multiphase acquisition protocol. Patients would benefit from a high-resolution imaging method capable of performing multi-phase imaging in a single acquisition without an increase in radiation dose. Spectral Photon-Counting Computed Tomography (SPCCT) has recently emerged as a novel and promising imaging modality in the field of diagnostic radiology. SPCCT is able to distinguish between two contrast agents referred to as multicolor imaging because, when measuring in three or more energy regimes, it can detect and quantify elements with a K-edge in the diagnostic energy range. Based on this capability, we tested the feasibility of a dual-contrast multi-phase liver imaging protocol via the use of iodinated and gadolinated contrast agents on four healthy New Zealand White (NZW) rabbits. To perform a dual-contrast protocol, we injected the agents at different times so that the first contrast agent visualized the portal phase and the second the arterial phase, both of which are mandatory for liver lesion characterization. We demonstrated a sensitive discrimination and quantification of gadolinium within the arteries and iodine within the liver parenchyma. In the hepatic artery, the concentration of gadolinium was much higher than iodine (8.5 ± 3.9 mg/mL versus 0.7 ± 0.1 mg/mL) contrary to the concentrations found in the liver parenchyma (0.5 ± 0.3 mg/mL versus 4.2 ± 0.3 mg/mL). In conclusion, our results confirm that SPCCT allows in-vivo dual contrast qualitative and quantitative multi-phase liver imaging in a single acquisition.

Effects of acquisition method and reconstruction algorithm for CT number measurement on standard-dose CT and reduced-dose CT: a QIBA phantom study.

To compare the effect of different acquisition and reconstruction methods on the radiation dose and accuracy of CT number measurements, using a 320-detector row CT and a Quantitative Imaging Biomarker Alliance (QIBA) recommended phantom. Acquisitions were performed on a 320-detector row CT, as 64- and 80-detector row helical and wide detector step-and-shoot (i.e., wide volume) acquisitions with tube currents of 400mA, 100mA, 50mA, 20mA, and 10mA. Image was reconstructed with the filtered back projection (FBP), adaptive iterative dose reduction using 3D processing (AIDR 3D), and forward projected model-based iterative reconstruction (FIRST) methods. The difference between measured CT numbers and the actual -856HU value of the phantom insert was determined by each CT acquisition protocol. Differences in actual and measured CT numbers were compared among acquisitions and among reconstruction methods by means of Tukey's HSD test. The CT number obtained with 64-detector row helical acquisition was significantly larger than that obtained with others (p < 0.0001). At each tube current, the CT number reconstructed with FIRST was significantly smaller than that with others (p < 0.0001). Acquisition and reconstruction methods are significantly affecting radiation dose reduction and accuracy of CT number measurements on a phantom study.

Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning.

Distinguishing between kidney stones and phleboliths can constitute a diagnostic challenge in patients undergoing unenhanced low-dose CT (LDCT) for acute flank pain. We sought to investigate the accuracy of radiomics and a machine-learning classifier in differentiating between kidney stones and phleboliths on LDCT. Radiomics features were extracted following a semi-automatic segmentation of kidney stones and phleboliths for two independent consecutive cohorts of patients undergoing LDCT for acute flank pain. Radiomics features from the first cohort of patients (n= 369) were ultimately used to train a machine-learning model designed to distinguish kidney stones (n= 211) from phleboliths (n= 201). Classification performance was assessed on the second independent cohort (i.e., testing set) (kidney stones n= 24; phleboliths n= 23) using positive and negative predictive values (PPV and NPV), area under the receiver operating curves (AUC), and permutation testing. Our machine-learning classification model trained on radiomics features achieved an overall accuracy of 85.1% on the independent testing set, with an AUC of 0.902, PPV of 81.5%, and NPV of 90.0%. Classification accuracy was significantly better than chance on permutation testing (p < 0.05, permutation p value). Radiomics and machine learning enable accurate differentiation between kidney stones and phleboliths on LDCT in patients presenting with acute flank pain. • Combining a machine-learning algorithm with radiomics features extracted for abdominopelvic calcification on LDCT offers a highly accurate method for discriminating phleboliths from kidney stones. • Our radiomics and machine-learning model proved robust for CT acquisition and reconstruction protocol when tested in comparison with an external independent cohort of patients with acute flank pain. • The high performance of the radiomics-based automatic classification model in differentiating phleboliths from kidney stones indicates its potential as a future diagnostic tool for equivocal abdominopelvic calcifications in the setting of suspected renal colic.

Cycle-consistent adversarial denoising network for multiphase coronary CT angiography.

In multiphase coronary CT angiography (CTA), a series of CT images are taken at different levels of radiation dose during the examination. Although this reduces the total radiation dose, the image quality during the low-dose phases is significantly degraded. Recently, deep neural network approaches based on supervised learning technique have demonstrated impressive performance improvement over conventional model-based iterative methods for low-dose CT. However, matched low- and routine-dose CT image pairs are difficult to obtain in multiphase CT. To address this problem, we aim at developing a new deep learning framework. We propose an unsupervised learning technique that can remove the noise of the CT images in the low-dose phases by learning from the CT images in the routine dose phases. Although a supervised learning approach is not applicable due to the differences in the underlying heart structure in two phases, the images are closely related in two phases, so we propose a cycle-consistent adversarial denoising network to learn the mapping between the low- and high-dose cardiac phases. Experimental results showed that the proposed method effectively reduces the noise in the low-dose CT image while preserving detailed texture and edge information. Moreover, thanks to the cyclic consistency and identity loss, the proposed network does not create any artificial features that are not present in the input images. Visual grading and quality evaluation also confirm that the proposed method provides significant improvement in diagnostic quality. The proposed network can learn the image distributions from the routine-dose cardiac phases, which is a big advantage over the existing supervised learning networks that need exactly matched low- and routine-dose CT images. Considering the effectiveness and practicability of the proposed method, we believe that the proposed can be applied for many other CT acquisition protocols.

Low-radiation and high image quality coronary computed tomography angiography in “real-world” unselected patients

AIMTo determine the radiation dose and image quality in coronary computed tomography angiography (CCTA) using state-of-the-art dose reduction methods in unselected “real world” patients.METHODSIn this single-centre study, consecutive patients in sinus rhythm underwent CCTA for suspected coronary artery disease (CAD) using a 320-row detector CT scanner. All patients underwent the standard CT acquisition protocol at our institute (Morriston Hospital) a combination of dose saving advances including prospective electrocardiogram-gating, automated tube current modulation, tube voltage reduction, heart rate reduction, and the most recent novel adaptive iterative dose reconstruction 3D (AIDR3D) algorithm. The cohort comprised real-world patients for routine CCTA who were not selected on age, body mass index, or heart rate. Subjective image quality was graded on a 4-point scale (4 = excellent, 1 = non-diagnostic).RESULTSA total of 543 patients were included in the study with a mean body weight of 81 ± 18 kg and a pre-scan mean heart rate of 70 ± 11 beats per minute (bpm). When indicated, patients received rate-limiting medication with an oral beta-blocker followed by additional intravenous beta-blocker to achieve a heart rate below 65 bpm. The median effective radiation dose was 0.88 mSv (IQR, 0.6-1.4 mSv) derived from a Dose Length Product of 61.45 mGy.cm (IQR, 42.86-100.00 mGy.cm). This also includes what we believe to be the lowest ever-reported radiation dose for a routine clinical CCTA (0.18 mSv). The mean image quality (± SD) was 3.65 ± 0.61, with a subjective image quality score of 3 (“good”) or above for 93% of patient CCTAs.CONCLUSIONCombining a low-dose scan protocol and AIDR3D with a 320-detector row CT scanner can provide high quality images at exceptionally low radiation dose in unselected patients being investigated for CAD.

Advanced CT acquisition protocol with a third-generation dual-source CT scanner and iterative reconstruction technique for comprehensive prosthetic heart valve assessment

ObjectivesMultidetector CT (MDCT) is a valuable tool for functional prosthetic heart valve (PHV) assessment. However, radiation exposure remains a concern. We assessed a novel CT-acquisition protocol for comprehensive PHV evaluation at limited dose.MethodsPatients with a PHV were scanned using a third-generation dual-source CT scanner (DSCT) and iterative reconstruction technique (IR). Three acquisitions were obtained: a non-enhanced scan; a contrast-enhanced, ECG-triggered, arterial CT angiography (CTA) scan with reconstructions at each 5 % of the R-R interval; and a delayed high-pitch CTA of the entire chest. Image quality was scored on a five-point scale. Radiation dose was obtained from the reported CT dose index (CTDI) and dose length product (DLP).ResultsWe analysed 43 CT examinations. Mean image quality score was 4.1±1.4, 4.7±0.5 and 4.2±0.6 for the non-contrast-enhanced, arterial and delayed acquisitions, respectively, with a total mean image quality of 4.3±0.7. Mean image quality for leaflet motion was 3.9±1.4. Mean DLP was 28.2±17.1, 457.3±168.6 and 68.5±47.2 mGy.cm for the non-contrast-enhanced (n=40), arterial (n=43) and delayed acquisition (n=43), respectively. The mean total DLP was 569±208 mGy.cm and mean total radiation dose was 8.3±3.0 mSv (n=43).ConclusionComprehensive assessment of PHVs is possible using DSCT and IR at moderate radiation dose.Key points• Prosthetic heart valve dysfunction is a potentially life-threatening condition.• Dual-source CT can adequately assess valve leaflet motion and anatomy.• We assessed a comprehensive protocol with three acquisitions for PHV evaluation.• This protocol is associated with good image quality and limited dose.

High Dose MicroCT Does Not Contribute Toward Improved MicroPET/CT Image Quantitative Accuracy and Can Limit Longitudinal Scanning of Small Animals

Obtaining accurate quantitative measurements in preclinical Positron Emission Tomography/Computed Tomography (PET/CT) imaging is of paramount importance in biomedical research and helps supporting efficient translation of preclinical results to the clinic. The purpose of this study was two-fold: (1) to investigate the effects of different CT acquisition protocols on PET/CT image quality and data quantification; and (2) to evaluate the absorbed dose associated with varying CT parameters. Methods: An air/water quality control CT phantom, tissue equivalent material phantom, an in-house 3D printed phantom and an image quality PET/CT phantom were imaged using a Mediso nanoPET/CT scanner. Collected data was analyzed using PMOD software, VivoQuant software and National Electric Manufactures Association (NEMA) software implemented by Mediso. Measured Hounsfield Unit (HU) in collected CT images were compared to the known HU values and image noise was quantified. PET recovery coefficients (RC), uniformity and quantitative bias were also measured. Results: Only less than 2% and 1% of CT acquisition protocols yielded water HU values < -80 and air HU values < -840, respectively. Four out of eleven CT protocols resulted in more than 100 mGy absorbed dose. Different CT protocols did not impact PET uniformity and RC, and resulted in <4% overall bias relative to expected radioactive concentration. Conclusion: Preclinical CT protocols with increased exposure times can result in high absorbed doses to the small animals. These should be avoided, as they do not contributed towards improved microPET/CT image quantitative accuracy and could limit longitudinal scanning of small animals.

Use of a channelized Hotelling observer to assess CT image quality and optimize dose reduction for iteratively reconstructed images.

The use of iterative reconstruction (IR) algorithms in CT generally decreases image noise and enables dose reduction. However, the amount of dose reduction possible using IR without sacrificing diagnostic performance is difficult to assess with conventional image quality metrics. Through this investigation, achievable dose reduction using a commercially available IR algorithm without loss of low contrast spatial resolution was determined with a channelized Hotelling observer (CHO) model and used to optimize a clinical abdomen/pelvis exam protocol. A phantom containing 21 low contrast disks-three different contrast levels and seven different diameters-was imaged at different dose levels. Images were created with filtered backprojection (FBP) and IR. The CHO was tasked with detecting the low contrast disks. CHO performance indicated dose could be reduced by 22% to 25% without compromising low contrast detectability (as compared to full-dose FBP images) whereas 50% or more dose reduction significantly reduced detection performance. Importantly, default settings for the scanner and protocol investigated reduced dose by upward of 75%. Subsequently, CHO-based protocol changes to the default protocol yielded images of higher quality and doses more consistent with values from a larger, dose-optimized scanner fleet. CHO assessment provided objective data to successfully optimize a clinical CT acquisition protocol.