Variation in CT Number and Image Noise Uniformity According to Patient Positioning in MDCT

Asynchronous calibration of a CT scanner for bone mineral density estimation: sources of error and correction

The estimation of BMD with CT scans requires a calibration method, usually based on a phantom. In asynchronous calibration, the phantom is scanned separately from the patient. A standardized acquisition protocol must be used to avoid variations between patient and phantom. However, variations can still be induced, for example, by temporal fluctuations or patient characteristics. Based on the further use of 739 forensic and 111 clinical CT scans, this study uses the proximal femur BMD value ("total hip") to assess asynchronous calibration accuracy, using in-scan calibration as ground truth. It identifies the parameters affecting the calibration accuracy and quantifies their impact. For time interval and table height, the impact was measured by calibrating the CT scan twice (once using the phantom scan with closest acquisition parameters and once using a phantom scan with standard values) and comparing the calibration accuracy. For other parameters such as body weight, the impact was measured by computing a linear regression between parameter values and calibration accuracy. Finally, this study proposes correction methods to reduce the effect of these parameters and improve the calibration accuracy. The BMD error of the asynchronous calibration, using the phantom scan with the closest acquisition parameters, was -1.2 ± 1.7% for the forensic and - 1.6 ± 3.5% for the clinical dataset. Among the parameters studied, time interval and body weight were identified as the main sources of error for asynchronous calibration, followed by table height and reconstruction kernel. Based on these results, a correction method was proposed to improve the calibration accuracy.

Misinterpretations about CT numbers, material decomposition, and elemental quantification

BACKGROUND

Quantitative CT imaging, particularly iodine and calcium quantification, is an important CT-based biomarker.

PURPOSE

This study quantifies sources of errors in quantitative CT imaging in both single-energy and spectral CT.

MATERIALS AND METHODS

This work examines the theoretical relationship between CT numbers, linear attenuation coefficient, and material quantification. We derive four understandings: (1) CT numbers are not proportional with element mass in vivo, (2) CT numbers are proportional with element mass only when contained in a voxel of pure water, (3) iodine-water material decomposition is never accurate in vivo, and (4) for error-free material decomposition a voxel must only consist of the basis decomposition vectors. Misinterpretation-based errors are calculated using the National Institute of Standards and Technology (NIST) XCOM database for: tissue chemical compositions, clinical concentrations of hydroxyapatite (HAP), and iodine. Quantification errors are also demonstrated experimentally using phantoms.

RESULTS

In single-energy CT, misinterpretation-induced errors for HAP density in adipose, muscle, lung, soft tissue, and blood ranged from 0-132%, i.e., a mass error of 0-749 mg/cm3. In spectral CT, errors with iodine in the same tissues resulted in a range of < 0.1-33% error, resulting in a mass error of < 0.1-1.2 mg/mL.

CONCLUSION

Our work demonstrates material quantification is fundamentally limited when measured in vivo due to measurement conditions differing from assumed and the errors are at or above detection limits for bone mineral density (BMD) and spectral iodine quantification. To define CT-derived biomarkers, the errors we demonstrate should either be avoided or built into uncertainty bounds.

CLINICAL RELEVANCE STATEMENT

Improving error bounds in quantitative CT biomarkers, specifically in iodine and BMD quantification, could lead to improvements in clinical care aspects based on quantitative CT.

KEY POINTS

CT numbers are only proportional with element mass only when contained in a voxel of pure water, therefore iodine-water material decomposition is never accurate in vivo. Misinterpretation-induced errors ranged from 0-132% for HAP density and < 0.1-33% in spectral CT with iodine. For error-free material decomposition, a voxel must only consist of the basis decomposition vectors.

The effects of distance between the imaging isocenter and brain center on the image quality of cone-beam computed tomography for brain stereotactic irradiation

In linear accelerator-based stereotactic irradiation (STI) for brain metastasis, cone-beam computed tomography (CBCT) image quality is essential for ensuring precise patient setup and tumor localization. However, CBCT images may be degraded by the deviation of the CBCT isocenter from the brain center. This study aims to investigate the effects of the distance from the brain center to the CBCT isocenter (DBI) on the image quality in STI. An anthropomorphic phantom was scanned with varying DBI in right, anterior, superior, and inferior directions. Thirty patients undergoing STI were prospectively recruited. Objective metrics, utilizing regions of interest included contrast-to-noise ratio (CNR) at the centrum semiovale, lateral ventricle, and basal ganglia levels, gray and white matter noise at the basal ganglia level, artifact index (AI), and nonuniformity (NU). Two radiation oncologists assessed subjective metrics. In this phantom study, objective measures indicated a degradation in image quality for non-zero DBI. In this patient study, there were significant correlations between the CNR at the centrum semiovale and lateral ventricle levels (rs = - 0.79 and - 0.77, respectively), gray matter noise (rs = 0.52), AI (rs = 0.72), and NU (rs = 0.91) and DBI. However, no significant correlations were observed between the CNR at the basal ganglia level, white matter noise, and subjective metrics and DBI (rs < ± 0.3). Our results demonstrate the effects of DBI on contrast, noise, artifacts in the posterior fossa, and uniformity of CBCT images in STI. Aligning the CBCT isocenter with the brain center can aid in improving image quality.

Prediction of proton stopping power ratios using dual-energy CT basis material decomposition

BACKGROUND

Proton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single-energy computed tomography (SECT). Various studies have shown that multi-energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age-related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection-based MECT systems for SPR prediction.

PURPOSE

To present and evaluate a novel proton SPR prediction method based on MD images from dual-energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy.

METHODS

A theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non-tissue materials, by minimizing the root-mean-square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD-SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data-fitting. The goodness of fit of the MD-SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head- and an abdomen-sized phantom setup, were acquired with a clinical projection-based fast-kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non-tissue materials in the phantoms, as well as used for input to the MD-SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image-based consecutive scan DECT for the same phantom setups.

RESULTS

The predicted SPRs of the tissue surrogates were similar for MD-SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non-adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between -0.7% and -1.8%. The SPRs of the non-tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD-SPR images, compared to 6.8% for DirectSPR.

CONCLUSIONS

The MD-SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non-tissue materials.

CT Number Accuracy and Association With Object Size: A Phantom Study Comparing Energy-Integrating Detector CT and Deep Silicon Photon-Counting Detector CT

BACKGROUND. Variable beam hardening based on patient size causes variation in CT numbers for energy-integrating detector (EID) CT. Photon-counting detector (PCD) CT more accurately determines effective beam energy, potentially improving CT number reliability. OBJECTIVE. The purpose of the present study was to compare EID CT and deep silicon PCD CT in terms of both the effect of changes in object size on CT number and the overall accuracy of CT numbers. METHODS. A phantom with polyethylene rings of varying sizes (mimicking patient sizes) as well as inserts of different materials was scanned on an EID CT scanner in single-energy (SE) mode (120-kV images) and in rapid-kilovoltage-switching dual-energy (DE) mode (70-keV images) and on a prototype deep silicon PCD CT scanner (70-keV images). ROIs were placed to measure the CT numbers of the materials. Slopes of CT number as a function of object size were computed. Materials' ideal CT number at 70 keV was computed using the National Institute of Standards and Technology XCOM Photon Cross Sections Database. The root mean square error (RMSE) between measured and ideal numbers was calculated across object sizes. RESULTS. Slope (expressed as Hounsfield units per centimeter) was significantly closer to zero (i.e., less variation in CT number as a function of size) for PCD CT than for SE EID CT for air (1.2 vs 2.4 HU/cm), water (-0.3 vs -1.0 HU/cm), iodine (-1.1 vs -4.5 HU/cm), and bone (-2.5 vs -10.1 HU/cm) and for PCD CT than for DE EID CT for air (1.2 vs 2.8 HU/cm), water (-0.3 vs -1.0 HU/cm), polystyrene (-0.2 vs -0.9 HU/cm), iodine (-1.1 vs -1.9 HU/cm), and bone (-2.5 vs -6.2 HU/cm) (p < .05). For all tested materials, PCD CT had the smallest RMSE, indicating CT numbers closest to ideal numbers; specifically, RMSE (expressed as Hounsfield units) for SE EID CT, DE EID CT, and PCD CT was 32, 44, and 17 HU for air; 7, 8, and 3 HU for water; 9, 10, and 4 HU for polystyrene; 31, 37, and 13 HU for iodine; and 69, 81, and 20 HU for bone, respectively. CONCLUSION. For numerous materials, deep silicon PCD CT, in comparison with SE EID CT and DE EID CT, showed lower CT number variability as a function of size and CT numbers closer to ideal numbers. CLINICAL IMPACT. Greater reliability of CT numbers for PCD CT is important given the dependence of diagnostic pathways on CT numbers.

Validation of deep learning-based CT image reconstruction for treatment planning

Deep learning-based CT image reconstruction (DLR) is a state-of-the-art method for obtaining CT images. This study aimed to evaluate the usefulness of DLR in radiotherapy. Data were acquired using a large-bore CT system and an electron density phantom for radiotherapy. We compared the CT values, image noise, and CT value-to-electron density conversion table of DLR and hybrid iterative reconstruction (H-IR) for various doses. Further, we evaluated three DLR reconstruction strength patterns (Mild, Standard, and Strong). The variations of CT values of DLR and H-IR were large at low doses, and the difference in average CT values was insignificant with less than 10 HU at doses of 100 mAs and above. DLR showed less change in CT values and smaller image noise relative to H-IR. The noise-reduction effect was particularly large in the low-dose region. The difference in image noise between DLR Mild and Standard/Strong was large, suggesting the usefulness of reconstruction intensities higher than Mild. DLR showed stable CT values and low image noise for various materials, even at low doses; particularly for Standard or Strong, the reduction in image noise was significant. These findings indicate the usefulness of DLR in treatment planning using large-bore CT systems.

Towards universal comparability of pericoronary adipose tissue attenuation: a coronary computed tomography angiography phantom study

OBJECTIVES

Different computed tomography (CT) scanners, variations in acquisition protocols, and technical parameters employed for image reconstruction may introduce bias in the analysis of pericoronary adipose tissue (PCAT) attenuation derived from coronary computed tomography angiography (CCTA). Therefore, the aim of this study was to establish the effect of tube voltage, measured as kilovoltage peak (kVp), and iterative reconstruction on PCAT mean attenuation (PCAT_MA).

METHODS

Twelve healthy ex vivo porcine hearts were injected with iodine-enriched agar-agar to allow for ex vivo CCTA imaging on a 256-slice CT and a dual-source CT system. Images were acquired at tube voltages of 80, 100, 120, and 140 kVp and reconstructed by using both filtered back projection and iterative reconstruction algorithms. PCAT_MA was measured semi-automatically on CCTA images in the proximal segment of coronary arteries.

RESULTS

The tube voltage showed a significant effect on PCAT_MA measurements on both the 256-slice CT scanner (p < 0.001) and the dual-source CT system (p = 0.013), resulting in higher attenuation values with increasing tube voltage. Similarly, the use of iterative reconstructions was associated with a significant increase of PCAT_MA (256-slice CT: p < 0.001 and dual-source CT: p = 0.014). Averaged conversion factors to correct PCAT_MA measurements for tube voltage other than 120 kVp were 1.267, 1.080 and 0.947 for 80, 100, and 140 kVp, respectively.

CONCLUSION

PCAT_MA values are significantly affected by acquisition and reconstruction parameters. The same tube voltage and reconstruction type are recommended when PCAT attenuation is used in multicenter and longitudinal studies.

KEY POINTS

• The tube voltage used for CCTA acquisition affects pericoronary adipose tissue attenuation, resulting in higher attenuation values of fat with increasing tube voltage. • Conversion factors for pericoronary adipose tissue attenuation values could be used to adjust for differences in attenuation between scans performed at different tube voltages. • In longitudinal CCTA studies employing pericoronary adipose tissue attenuation as imaging endpoint, it is recommended to maintain tube voltage and image reconstruction type constant across serial scans.

Influence of Pitch on Surface Dose Distribution and Image Noise of Computed Tomography Scans

This study evaluated the effect of pitch on 256-slice helical computed tomography (CT) scans. Cylindrical water phantoms (CWP) were measured using axial and helical scans with various pitch values. The surface dose distributions of CWP were measured, and reconstructed images were obtained using filtered back-projection (FBP) and iterative model reconstruction (IMR). The image noise in each reconstructed image was decomposed into a baseline component and another component that varied along the z-axis. The baseline component of the image noise was highest at the center of the reconstructed image and decreased toward the edges. The normalized 2D power spectra for each pitch were almost identically distributed. Furthermore, the ratios of the 2D power spectra for IMR and FBP at different pitch values were obtained. The magnitudes of the components varying along the z-axis were smallest at the center of the reconstructed image and increased toward the edge. The ratios of the 3D power spectra on the f_x axis for IMR and FBP at different pitch values were obtained. The results showed that the effect of the pitch was related to the component that varied along the z-axis. Furthermore, the pitch had a smaller effect on IMR than on FBP.

The effect of computed tomography parameters on sarcopenia and myosteatosis assessment: a scoping review

Computed tomography (CT) is a valuable assessment method for muscle pathologies such as sarcopenia, cachexia, and myosteatosis. However, several key underappreciated scan imaging parameters need consideration for both research and clinical use, specifically CT kilovoltage and the use of contrast material. We conducted a scoping review to assess these effects on CT muscle measures. We reviewed articles from PubMed, Scopus, and Web of Science from 1970 to 2020 on the effect of intravenous contrast material and variation in CT kilovoltage on muscle mass and density. We identified 971 articles on contrast and 277 articles on kilovoltage. The number of articles that met inclusion criteria for contrast and kilovoltage was 11 and 7, respectively. Ten studies evaluated the effect of contrast on muscle density of which nine found that contrast significantly increases CT muscle density (arterial phase 6-23% increase, venous phase 19-57% increase, and delayed phase 23-43% increase). Seven out of 10 studies evaluating the effect of contrast on muscle area found significant increases in area due to contrast (≤2.58%). Six studies evaluating kilovoltage on muscle density found that lower kilovoltage resulted in a higher muscle density (14-40% increase). One study reported a significant decrease in muscle area when reducing kilovoltage (2.9%). The use of contrast and kilovoltage variations can have dramatic effects on skeletal muscle analysis and should be considered and reported in CT muscle analysis research. These significant factors in CT skeletal muscle analysis can alter clinical and research outcomes and are therefore a barrier to clinical application unless better appreciated.

Photon count rates estimated from 1980 clinical CT scans

BACKGROUND

All photon counting detectors have a characteristic count rate over which their performance degrades. Degradation in the clinical setting takes the form of increased noise, reduced material quantification accuracy, and image artifacts. Count rate is a function of patient attenuation, beam filtration, scanner geometry, and X-ray technique.

PURPOSE

To guide protocol and technology development in the photon counting space, knowledge of clinical count rates spanning the complete range of clinical indications and patient sizes is needed. In this paper, we use clinical data to characterize the range of computed tomography (CT) count rates.

METHODS

We retrospectively gathered 1980 patient exams spanning the entire body (head/neck/chest/abdomen/extremity) and sampled 36 951 axial image slices. We assigned the tissue labels air/lung/fat/soft tissue/bone to each voxel for each slice using CT number thresholds. We then modeled four different bowtie filters, 70/80/100/120/140 kV spectra, and a range of mA values. We forward-projected each slice to obtain detector-incident count rates, using the geometry of a GE Revolution Apex scanner. Our analysis divided the detector into thirds: the central one-third, one-third of the detector split into two equal regions adjacent to the central third, and the final one-third divided equally between the outer detector edges. We report the 99th percentile of counts to mimic the upper limits of count rates making passing through a patient as a function of patient water equivalent diameter. We also report the percentage of patient scans, by body region, over different count rate thresholds for all combinations of bowtie and beam energy.

RESULTS

For routine exam types, we recorded count rates of approximately 3.5 × 10⁸  counts/mm² /s in the torso, extremities, and brain. For neck scans, we observed count rates near 6 × 10⁸  counts/mm² /s. Our simulations of 1000 mA, appropriately mimicking the mA needs for fast pediatric, fast thoracic, and cardiac scanning, resulted in count rates of over 10 × 10⁸  counts/mm² /s for the torso, extremities, and brain. At 1000 mA, for the neck region, we observed count rates close to 2 × 10⁹  counts/mm² /s. Importantly, we saw only a small change in maximum count rate needs over patient size, which we attribute to patient mis-positioning with respect to the bowtie filters. As expected, combinations of kV and bowtie filter with higher beam energies and wider/less attenuating bowtie fluence profiles lead to higher count rates relative to lower energies. The 99th-50th percentile count rate changed the most for the torso region, with a maximum variation of 3.9 × 10⁸ to 1.2 × 10⁷  counts/mm² /s. The head/neck/extremity regions had less than a 50% change in count rate from the 99th to 50th percentiles.

CONCLUSIONS

Our results are the first to use a large patient cohort spanning all body regions to characterize count rates in CT. Our results should be useful in helping researchers understand count rates as a function of body region and mA for various combinations of bowtie filter designs and beam energies. Our results indicate clinical rates >1 × 10⁹  counts/mm² /s, but they do not predict the image quality impact of using a detector with lower characteristic count rates.

Distinguishing pancreatic solid serous cystadenomas from nonfunctional pancreatic neuroendocrine tumors by computed tomography: A propensity score analysis

This study aims to evaluate the utility of calculated computed tomography (CT) attenuation value ratio (AVR) and enhancement pattern in distinguishing pancreatic solid serous cystadenomas (SCAs) from nonfunctional pancreatic neuroendocrine tumors (NF-pNETs). A total of 142 consecutive patients with 22 solid SCAs and 120 NF-pNETs confirmed by pathology were included in this retrospective study. All patients underwent preoperative contrast-enhanced CT and were categorized into 2 groups, solid SCA and NF-pNET groups. Patients with NF-pNETs were matched to patients with solid SCAs via propensity scores. AVR was measured and defined as: attenuation value of tumor/attenuation value of normal pancreas. AVR and enhancement pattern performance were assessed according to the discriminative abilities of patients. After matching, 29 patients were allocated to the NF-pNET group. Before matching, sex, age, and the peak enhanced value phase were significantly different between solid SCA and NF-pNET patients (P < .05). After matching, no significant difference was observed between both groups (P > .05). Solid SCAs AVRs were significantly smaller than NF-pNETs AVRs in all unenhanced, arterial, portal venous, and delayed phases (P < .05). Solid SCAs showed significantly more wash-in and wash-out enhancement patterns than NF-pNETs (P < .05). For unenhanced, arterial, portal venous, and delayed phases, and enhancement pattern, the area under the curve (AUC) values were 0.96, 0.72, 0.80, 0.85, and 0.86, respectively. Low AVR on unenhanced CT and wash-in and wash-out enhancement patterns were useful for differentiating solid SCAs from NF-pNETs and may be useful for clinical decisions, a clearer opinion will be formed with further studies to be conducted with larger patient numbers.

The Impact of Parameter Selection and Setup Conditions on Image Quality of an On-Board Helical Kilovoltage Computed Tomography System

Purpose

To evaluate the imaging performance of an on-board helical kilovoltage computed tomography (kVCT) system mounted on a helical tomotherapy unit for various imaging parameters and setup conditions.

Methods

Images of a commonly used computed tomography (CT) image quality phantom were acquired while varying the selection of available parameters (anatomy, mode, body size) as well as phantom positioning and size. Image quality metrics (IQM) including noise, uniformity, contrast, CT number constancy, and spatial resolution were compared for parameter and setup variations. 

Results

The use of fine mode improved noise and contrast metrics by 20-30% compared to normal mode and by nearly a factor of two compared to the coarse mode for otherwise identical protocols. Uniformity, CT number constancy, and spatial resolution were also improved for fine mode. Thorax and pelvis anatomy protocols improved noise, uniformity, and contrast metrics by 10-20% compared to images acquired with head protocols. No significant differences in CT number constancy or spatial resolution were observed regardless of anatomy choice. Increasing body size (milliampere second (mAs)/rotation) improved each image quality metric. Vertical and lateral phantom shifts of up to ±6 cm degraded noise and contrast metrics by up to 30% relative to the isocenter while also worsening uniformity and CT number constancy. IQM were also degraded substantially with the use of annuli to increase the phantom diameter (32 cm vs. 20 cm). Despite variations in image characteristics among the investigated changes, most metrics were within manufacturer specifications when applicable.

Conclusion

This work demonstrates the dependence of image quality on parameter selection and setup conditions for a helical kVCT system utilized in image-guided and adaptive helical tomotherapy treatments. While the overall image quality is robust to variations in imaging parameters, care should be taken when selecting parameters as patient size increases or positioning moves from the isocenter to ensure adequate image quality is still achieved.

The Impacts of Vertical Off-Centring, Localiser Direction, Phantom Positioning and Tube Voltage on CT Number Accuracy: An Experimental Study

Background: This study investigates the effects of vertical off-centring, localiser direction, tube voltage, and phantom positioning (supine and prone) on computed tomography (CT) numbers and radiation dose. Methods: An anthropomorphic phantom was scanned using a Discovery CT750 HD—128 slice (GE Healthcare) scanner at different tube voltages (80, 120, and 140 kVp). Images employing 0° and 180° localisers were acquired in supine and prone positions for each vertical off-centring (±100, ±60, and ±30 mm from the iso-centre). CT numbers and displayed volume CT dose index (CTDIvol) were recorded. The relationship between dose variation and CT number was investigated. Results: The maximum changes in CT number between the two phantom positions as a function of vertical-off-centring were for the upper thorax 34 HU (0° localiser, 120 kVp), mid thorax 43 HU (180° localiser, 80 kVp), and for the abdominal section 31 HU (0° localiser, 80 kVp) in the prone position. A strong positive correlation was reported between the variation in dose and CT number (r = 0.969, p < 0.001); 95% CI (0.93, 0.99). Conclusions: Patient positioning demands an approach with a high degree of accuracy, especially in cases where clinical decisions depend on CT number accuracy for tissue lesion characterisation.

The impacts of vertical off-centring, tube voltage, and phantom size on computed tomography numbers: An experimental study

INTRODUCTION

This experimental study explored the effect of vertical off-centring on computed tomography (CT) numbers in combination with various tube voltages and phantom sizes for two CT units.

METHODS

CIRS Model 062 Electron Density and system performance phantoms were imaged on Siemens Emotion 16-slice CT and GEMINI-GXL scanners, respectively. Uniformity and accuracy were evaluated as a function of vertical off-centring (20, 40, 60, and 80 mm above the gantry isocentre) using different water phantom sizes (18, 20, and 30 cm) and tube voltages (80, 90, 110, 120, 130 and 140 kVp).

RESULTS

Vertical off-centring and phantom size accounted for 92% of the recorded variance and the resultant change in CT numbers. The uniformity test recorded maximum changes of 14 and 27.2 HU for peripheral ROIs across the X- and Y-axes for an 80 mm phantom shift above the gantry isocentre on the GEMINI GXL and Siemens scanners, respectively. The absolute CT number differences between the superior and inferior ROIs were 13.7 HU for the 30 cm phantom and 4.8 HU for the 20 cm phantom for 80 mm vertical off-centring. The largest differences were observed at lower tube voltages.

CONCLUSIONS

It is essential to highlight the significance of CT number variation in clinical decision-making. Phantom off-centring affected the uniformity of these numbers, which were further impacted by the ROI position in this experimental study. CT number variation was more evident in peripheral phantom areas, lower tube voltages and larger phantom sizes.

IMPLICATIONS FOR PRACTICE

CT number is observed to be a variable under certain common conditions. This significantly impacts several applications where clinical decisions depend on CT number accuracy for tissue lesion characterisation.

Value-added Opportunistic CT Screening: State of the Art

Opportunistic CT screening leverages robust imaging data embedded within abdominal and thoracic scans that are generally unrelated to the specific clinical indication and have heretofore gone largely unused. This incidental imaging information may prove beneficial to patients in terms of wellness, prevention, risk profiling, and presymptomatic detection of relevant disease. The growing interest in CT-based opportunistic screening relates to a confluence of factors: the objective and generalizable nature of CT-based body composition measures, the emergence of fully automated explainable AI solutions, the sheer volume of body CT scans performed, and the increasing emphasis on precision medicine and value-added initiatives. With a systematic approach to body composition and other useful CT markers, initial evidence suggests that their ability to help radiologists assess biologic age and predict future adverse cardiometabolic events rivals even the best available clinical reference standards. Emerging data suggest that standalone "intended" CT screening over an unorganized opportunistic approach may be justified, especially when combined with established cancer screening. This review will discuss the current status of opportunistic CT screening, including specific body composition markers and the various disease processes that may be impacted. The remaining hurdles to widespread clinical adoption include generalization to more diverse patient populations, disparate technical settings, and reimbursement.

The Improvement of Patient Centering in Computed Tomography Through a Technologist-Focused Education Initiative

Proper patient centering is fundamental to the operation of CT. Misalignment of the patient is known to have a negative impact on image quality and dose. The purpose of this study was to improve patient centering in CT and examine the efficacy of several educational methods that could be implemented at any clinical site. The IRB determined the study was not human subjects research, and oversight was waived. Three interventions were examined. The first intervention involved a discussion on patient centering at a staff meeting. As the second intervention, an educational presentation was developed and delivered to CT technologists addressing the physics behind the importance of patient centering in CT. As the third intervention, individual technologist centering performance reviews were conducted by the modality supervisor. Clinical scan data was collected for each study period via a cloud-based software to examine the efficacy of each intervention in terms of lateral and vertical offset. The mean vertical offset of the baseline data was -1.97 cm. After the staff meeting, the mean vertical offset decreased to -1.60 cm (p < 0.001). Following the educational presentation, the mean vertical offset decreased to -1.14 cm (p < 0.001). After the technologist performance reviews, the mean vertical offset decreased to -0.86 cm (p < 0.001). This research examined a quality improvement initiative to improve patient centering at our institution which focused on communication and education. Through this initiative, the mean vertical positioning error decreased, the percentage of exams within 0-1 cm of isocenter increased, and the percentage of exams misaligned by greater than 3 cm decreased. This work has shown that patient centering can be improved with education.

A novel simulation-driven reconstruction approach for X-ray computed tomography

PURPOSE

Radiation dose reduction is critical to the success of x-ray computed tomography (CT). Many advanced reconstruction techniques have been developed over the years to combat noise resulting from the low-dose CT scans. These algorithms rely on accurate local estimation of the image noise to determine reconstruction parameters or to select inferencing models. Because of difficulties in the noise estimation for heterogeneous objects, the performance of many algorithms is inconsistent and suboptimal. In this paper, we propose a novel approach to overcome such shortcoming.

METHOD

By injecting appropriate amount of noise in the CT raw data, a computer simulation approach is capable of accurately estimating the local statistics of the raw data and the local noise in the reconstructed images. This information is then used to guide the noise reduction process during the reconstruction. As an initial implementation, a scaling map is generated based on the noise predicted from the simulation and the noise estimated from existing reconstruction algorithms. Images generated with existing algorithms are subsequently modified based on the scaling map. In this study, both iterative reconstruction (IR) and deep learning image reconstruction (DLIR) algorithms are evaluated.

RESULTS

Phantom experiments were conducted to evaluate the performance of the simulation-based noise estimation in terms of the standard deviation and noise power spectrum (NPS). Quantitative results have demonstrated that the noise measured from the original image matches well with the noise estimated from the simulation. Clinical datasets were utilized to further confirm the accuracy of the proposed approach under more challenging conditions. To validate the performance of the proposed reconstruction approach, clinical scans were used. Performance comparison was carried out qualitatively and quantitatively. Two existing advanced reconstruction techniques, IR and DLIR, were evaluated against the proposed approach. Results have shown that the proposed approach outperforms existing IR and DLIR algorithms in terms of noise suppression and, equally importantly, noise uniformity across the entire imaging volume. Visual assessment of the images also reveals that the proposed approach does not endure noise texture issues facing some of the existing reconstruction algorithms today.

CONCLUSION

Phantom and clinical results have demonstrated superior performance of the proposed approach with regard to noise reduction as well as noise homogeneity. Visual inspection of the noise texture further confirms the clinical utility of the proposed approach. Future enhancements on the current implementation are explored regarding image quality and computational efficiency. Because of the limited scope of this paper, detailed investigation on these enhancement features will be covered in a separate report. This article is protected by copyright. All rights reserved.

The reliability of CT numbers as absolute values for diagnostic scanning, dental imaging, and radiation therapy simulation: A narrative review

BACKGROUND AND PURPOSE

The purpose of this review was to examine the reported factors that affect the reliability of Computed Tomography (CT) numbers and their impact on clinical applications in diagnostic scanning, dental imaging, and radiation therapy dose calculation.

METHODS

A comprehensive search of the literature was conducted using Medline (PubMed), Google Scholar, and Ovid databases which were searched using the keywords CT number variability, CT number accuracy and uniformity, tube voltage, patient positioning, patient off-centring, and size dependence. A narrative summary was used to compile the findings under the overarching theme.

DISCUSSION

A total of 47 articles were identified to address the aim of this review. There is clear evidence that CT numbers are highly dependent on the energy level applied based on the effective atomic number of the scanned tissue. Furthermore, body size and anatomical location have also indicated an influence on measured CT numbers, especially for high-density materials such as bone tissue and dental implants. Patient off-centring was reported during CT imaging, affecting dose and CT number reliability, which was demonstrated to be dependent on the shaping filter size.

CONCLUSION

CT number accuracy for all energy levels, body sizes, anatomical locations, and degrees of patient off-centring is observed to be a variable under certain common conditions. This has significant implications for several clinical applications. It is crucial for those involved in CT imaging to understand the limitations of their CT system to ensure radiologists and operators avoid potential pitfalls associated with using CT numbers as absolute values for diagnostic scanning, dental imaging, and radiation therapy dose calculation.

Impacts of Phantom Off-Center Positioning on CT Numbers and Dose Index CTDIv: An Evaluation of Two CT Scanners from GE

The purpose of this work is to evaluate the impacts of body off-center positioning on CT numbers and dose index CTDIv of two scanners from GE. HD750 and APEX scanners were used to acquire a PBU60 phantom of Kagaku and a 062M phantom of CIRS respectively. CT images were acquired at various off-center positions under automatic tube current modulation using various peak voltages. CTDIv were recorded for each of the acquisitions. An abdomen section of the PBU60 phantom was used for CT number analysis and tissue inserts of the 062M phantom were filled with water balloons to mimic the human abdomen. CT numbers of central regions of interests were averaged using the Fiji software. As phantoms were lifted above the iso-center, both CTDIv and CT numbers were increased for the HD750 scanner whilst they were approximately constant for the APEX scanner. The measured sizes of anterior-posterior projection images were also increased for both scanners whilst the sizes of lateral projection images were increased for the HD750 scanner but decreased for the APEX scanner. Off-center correction algorithms were implemented in the APEX scanner. Matching the X-ray projection center with the system's iso-center could improve the accuracy of CT imaging.

Sources of error in bone mineral density estimates from quantitative CT

Bone mineral density (BMD) estimates from quantitative computed tomography (QCT) have proven useful for opportunistic screening of osteoporosis, treatment monitoring, and bone strength measurement. These estimates are subject to bias and variance from a variety of sources related to the imaging equipment, methods applied in the estimation procedure, and the patients themselves. In this article, we review the literature to describe the sources and sizes of error in spine and hip BMD estimates from single-energy QCT that can result from factors related to the scanner, imaging techniques, imaging subject, calibration phantom, and calibration approach. We also describe the baseline variance that can be expected based on repeatability and reproducibility studies. Though reproducible BMD estimates may be achievable with QCT, a thorough understanding of the potential sources of error and their size relative to the diagnostic task is essential to their appropriate and meaningful interpretation.

Influence of breathing state on the accuracy of automated patient positioning in thoracic CT using a 3D camera for body contour detection

Objective

To assess the influence of breathing state on the accuracy of a 3D camera for body contour detection and patient positioning in thoracic CT.

Materials and methods

Patients who underwent CT of the thorax with both an inspiratory and expiratory scan were prospectively included for analysis of differences in the ideal table height at different breathing states. For a subgroup, an ideal table height suggestion based on 3D camera images at both breathing states was available to assess their influence on patient positioning accuracy. Ideal patient positioning was defined as the table height at which the scanner isocenter coincides with the patient’s isocenter.

Results

The mean (SD) difference of the ideal table height between the inspiratory and the expiratory breathing state among the 64 included patients was 10.6 mm (4.5) (p < 0.05). The mean (SD) positioning accuracy, i.e., absolute deviation from the ideal table height, within the subgroup (n = 43) was 4.6 mm (7.0) for inspiratory scans and 7.1 mm (7.7) for expiratory scans (p < 0.05) when using corresponding 3D camera images. The mean (SD) accuracy was 14.7 mm (7.4) (p < 0.05) when using inspiratory camera images on expiratory scans; vice versa, the accuracy was 3.1 mm (9.5) (p < 0.05).

Conclusion

A 3D camera allows for accurate and precise patient positioning if the camera image and the subsequent CT scan are acquired in the same breathing state. It is recommended to perform an expiratory planning image when acquiring a thoracic CT scan in both the inspiratory and expiratory breathing state.

Key Points

• A 3D camera for body contour detection allows for accurate and precise patient positioning if the camera image and the subsequent CT scan are acquired in the same breathing state.

• It is recommended to perform an expiratory planning image when acquiring a thoracic CT scan in both the inspiratory and expiratory breathing state.

Quality control of radiomic features using 3D-printed CT phantoms

Purpose: The lack of standardization in quantitative radiomic measures of tumors seen on computed tomography (CT) scans is generally recognized as an unresolved issue. To develop reliable clinical applications, radiomics must be robust across different CT scan modes, protocols, software, and systems. We demonstrate how custom-designed phantoms, imprinted with human-derived patterns, can provide a straightforward approach to validating longitudinally stable radiomic signature values in a clinical setting. Approach: Described herein is a prototype process to design an anatomically informed 3D-printed radiomic phantom. We used a multimaterial, ultra-high-resolution 3D printer with voxel printing capabilities. Multiple tissue regions of interest (ROIs), from four pancreas tumors, one lung tumor, and a liver background, were extracted from digital imaging and communication in medicine (DICOM) CT exam files and were merged together to develop a multipurpose, circular radiomic phantom (18 cm diameter and 4 cm width). The phantom was scanned 30 times using standard clinical CT protocols to test repeatability. Features that have been found to be prognostic for various diseases were then investigated for their repeatability and reproducibility across different CT scan modes. Results: The structural similarity index between the segment used from the patients' DICOM image and the phantom CT scan was 0.71. The coefficient variation for all assessed radiomic features was < 1.0 % across 30 repeat scans of the phantom. The percent deviation (pDV) from the baseline value, which was the mean feature value determined from repeat scans, increased with the application of the lung convolution kernel, changes to the voxel size, and increases in the image noise. Gray level co-occurrence features, contrast, dissimilarity, and entropy were particularly affected by different scan modes, presenting with pDV > ± 15 % . Conclusions: Previously discovered prognostic and popular radiomic features are variable in practice and need to be interpreted with caution or excluded from clinical implementation. Voxel-based 3D printing can reproduce tissue morphology seen on CT exams. We believe that this is a flexible, yet practical, way to design custom phantoms to validate and compare radiomic metrics longitudinally, over time, and across systems.

Protocol Optimization Considerations for Implementing Deep Learning CT Reconstruction

OBJECTIVE. Previous advances over filtered back projection (FBP) have incorporated model-based iterative reconstruction. The purpose of this study was to characterize the latest advance in image reconstruction, that is, deep learning. The focus was on applying characterization results of a deep learning approach to decisions about clinical CT protocols. MATERIALS AND METHODS. A proprietary deep learning image reconstruction (DLIR) method was characterized against an existing advanced adaptive statistical iterative reconstruction method (ASIR-V) and FBP from the same vendor. The metrics used were contrast-to-noise ratio, spatial resolution as a function of contrast level, noise texture (i.e., noise power spectra [NPS]), noise scaling as a function of slice thickness, and CT number consistency. The American College of Radiology accreditation phantom and a uniform water phantom were used at a range of doses and slice thicknesses for both axial and helical acquisition modes. RESULTS. ASIR-V and DLIR were associated with improved contrast-to-noise ratio over FBP for all doses and slice thicknesses. No dose or contrast dependencies of spatial resolution were observed for ASIR-V or DLIR. NPS results showed DLIR maintained an FBP-like noise texture whereas ASIR-V shifted the NPS to lower frequencies. Noise changed with dose and slice thickness in the same manner for ASIR-V and FBP. DLIR slice thickness noise scaling differed from FBP, exhibiting less noise penalty with decreasing slice thickness. No clinically significant changes were observed in CT numbers for any measurement condition. CONCLUSION. In a phantom model, DLIR does not suffer from the concerns over reduction in spatial resolution and introduction of poor noise texture associated with previous methods.

A comparison between manual and artificial intelligence-based automatic positioning in CT imaging for COVID-19 patients

Objective

To analyze and compare the imaging workflow, radiation dose, and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method.

Materials and methods

One hundred twenty-seven adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time, and off-center distance of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups.

Results

The AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP 1.56 cm ± 0.83 vs. MP 4.05 cm ± 2.40, p < 0.001) and higher proportion of positioning accuracy (AP 99% vs. MP 92%), resulting in 16% radiation dose reduction (AP 6.1 mSv ± 1.3 vs. MP 7.3 mSv ± 1.2, p < 0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas.

Conclusion

The AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose and optimizing imaging workflow and image quality in imaging the chest.

Key Points

• The AI-based automatic positioning (AP) operation was successful for all patients in our study.

• AP method reduced the total positioning time by 28% compared with the manual positioning (MP).

• AP method had less patient off-center distance and higher proportion of positioning accuracy than MP method, resulting in 16% radiation dose reduction and 9% image noise reduction in erector spinae.

Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses

Osteoporosis affects an increasing number of people every year and patient specific finite element analysis of the femur has been proposed to identify patients that could benefit from preventative treatment. The aim of this study was to demonstrate, verify, and validate an objective process for selecting tissues for use as the basis of phantomless calibration to enable patient specific finite element analysis derived hip fracture risk prediction. Retrospective reanalysis of patient computed tomography (CT) scans has the potential to yield insights into more accurate prediction of osteoporotic fracture. Bone mineral density (BMD) specific calibration scans are not typically captured during routine clinical practice. Tissue-based BMD calibration can therefore empower the retrospective study of patient CT scans captured during routine clinical practice. Together the method for selecting tissues as the basis for phantomless calibration coupled with the post-processing steps for deriving a calibration equation using the selected tissues provide an estimation of quantitative equivalent density results derived using calibration phantoms. Patient tissues from a retrospective cohort of 211 patients were evaluated. The best phantomless calibration resulted in a femoral strength (FS) [N] bias of 0.069 ± 0.07% over FS derived from inline calibration and a BMD [kg/cm³] bias of 0.038 ± 0.037% over BMD derived from inline calibration. The phantomless calibration slope for the best method presented was within the range of patient specific calibration curves available for comparison and demonstrated a small bias of 0.028 ± 0.054 HU/(mg/cm³), assuming the Mindways Model 3 BMD inline calibration phantom as the gold standard. The presented method of estimating a calibration equation from tissues showed promise for CT-based femoral fracture analyses of retrospective cohorts without readily available calibration data.

Body size and tube voltage dependent corrections for Hounsfield Unit in medical X-ray computed tomography: theory and experiments

The purpose of this work is to present a body size and tube voltage dependent correction scheme for the Hounsfield Unit, HU, in medical X-ray Computed Tomography imaging. Boltzmann photon transport equation was employed to study X-ray interaction with bulk water in CT imaging. Experimentally measured X-ray output in body of phantoms and attenuation cross sections of water were employed in the derivation of beam intensity in X-ray imaging. A Somatom Emotion CT scanner from Siemens and electron density phantoms from CIRS were employed to acquire CT images of different body sizes and different tissue materials located at different depths from body’s surface. Tube voltage and depth dependent effective attenuation of bulk water was found from theoretical analysis in agreement with measured size-specific correction factors for CTDI_vol under different tube voltages. A size and tube voltage dependent correction scheme for the Hounsfield Unit is established. For the same tissue material, body size has much larger impact on the CT number variations than that of depth from the body surface in phantom measurements. Good results were achieved by applying the established correction scheme on the experimentally measured CT number variations under different tube voltages and body sizes.

Influence of feature calculating parameters on the reproducibility of CT radiomic features: a thoracic phantom study

Background

Existing studies have demonstrated that imaging parameters may affect radiomic features. However, the influence of feature calculating parameters has been overlooked. The purpose of this study is to investigate the influence of feature calculating parameters (gray-level range and bin size) on the reproducibility of CT radiomic features.

Methods

Thirty-six CT scans from an anthropomorphic thoracic phantom were acquired with different imaging parameters including effective dose, pitch, slice thicknesses and reconstruction kernels. The influence of feature calculating parameters was investigated in terms of three gray-level ranges and eleven gray-level bin sizes. Feature reproducibility was assessed by the intraclass correlation coefficient (ICC) with the cutoff value of 0.8 and the coefficient of variation (CV) with the cutoff value of 20%. The agreements of reproducible features in different ranges and bin sizes were analyzed by Kendall's W test and Kappa test. The proportions of reproducible features, in terms of two calculating, four imaging and two segmentation parameters, were evaluated using Cochran's Q test and Dunn's test.

Results

For the three gray-level ranges, 50% (44/88) of features were reproducible with a perfect agreement (Kendall's W coefficient 0.844, P<0.001). Of the 72 features that may be influenced by gray-level bin size, 33.3% (24/72) were reproducible for 11 bin sizes with a perfect agreement (Kendall's W coefficient 0.879, P<0.001). For the proportions of reproducible features, there was no statistically significant difference among three ranges (P=0.420), but there was among eleven bin sizes (P=0.013). The proportions of reproducible features in feature calculating parameters were statistically significantly lower than those in imaging parameters (adjusted P<0.05).

Conclusions

Feature calculating parameters may have a greater influence than imaging parameters on the reproducibility of CT radiomic features, which should be given special attention in clinical applications.

The z-sbDBA, a new concept for a dynamic sheet-based fluence field modulator in x-ray CT

PURPOSE

We present a new concept for dynamic fluence field modulation (FFM) in x-ray computed tomography (CT). The so-called z-aligned sheet-based dynamic beam attenuator (z-sbDBA) is developed to dynamically compensate variations in patient attenuation across the fan beam and the projection angle. The goal is to enhance image quality and to reduce patient radiation dose.

METHODS

The z-sbDBA consists of an array of attenuation sheets aligned along the z direction. In neutral position, the array is focused toward the focal spot. Tilting the z-sbDBA defocuses the sheets, thus reducing the transmission for larger fan beam angles. The structure of the z-sbDBA significantly differs from the previous sheet-based dynamic beam attenuator (sbDBA) in two features: (a) The sheets of the z-sbDBA are aligned parallel to the detector rows, and (b) the height of the sheets increases from the center toward larger fan beam angles. We built a motor actuated prototype of the z-sbDBA integrated into a clinical CT scanner. In experiments, we investigated its feasibility for FFM. We compared the z-sbDBA to common CT bowtie filters in terms of the spectral dependency of the transmission and possible image variance distribution in reconstructed phantom images. Additionally, the potential radiation dose saving using z-sbDBA for region-of-interest (ROI) imaging was studied.

RESULTS

Our experimental results confirm that the z-sbDBA can realize variable transmission profiles of the radiation fluence by only small tilts. Compared to the sbDBA, the z-sbDBA can mitigate some practical and mechanical issues. In comparison to bowtie filters, the spectral dependency is considerably reduced when using the z-sbDBA. Likewise, more homogeneous image variance distributions can be attained in reconstructed phantom images. The z-sbDBA allows controlling the spatial image variance distribution which makes it suitable for ROI imaging. Our comparison on ROI imaging reveals skin dose reductions of up to 35% at equal ROI image quality by using the z-sbDBA.

CONCLUSION

Our new concept for FFM in x-ray CT, the z-sbDBA, was experimentally validated on a clinical CT scanner. It facilitates dynamic FFM by realizing variable transmission profiles across the fan beam angle on a projection-wise basis. This key feature allows for substantial improvements in image quality, a reduction in patient radiation dose, and additionally provides a technical solution for ROI imaging.

Multi-energy computed tomography and material quantification: Current barriers and opportunities for advancement

Computed tomography (CT) technology has rapidly evolved since its introduction in the 1970s. It is a highly important diagnostic tool for clinicians as demonstrated by the significant increase in utilization over several decades. However, much of the effort to develop and advance CT applications has been focused on improving visual sensitivity and reducing radiation dose. In comparison to these areas, improvements in quantitative CT have lagged behind. While this could be a consequence of the technological limitations of conventional CT, advanced dual-energy CT (DECT) and photon-counting detector CT (PCD-CT) offer new opportunities for quantitation. Routine use of DECT is becoming more widely available and PCD-CT is rapidly developing. This review covers efforts to address an unmet need for improved quantitative imaging to better characterize disease, identify biomarkers, and evaluate therapeutic response, with an emphasis on multi-energy CT applications. The review will primarily discuss applications that have utilized quantitative metrics using both conventional and DECT, such as bone mineral density measurement, evaluation of renal lesions, and diagnosis of fatty liver disease. Other topics that will be discussed include efforts to improve quantitative CT volumetry and radiomics. Finally, we will address the use of quantitative CT to enhance image-guided techniques for surgery, radiotherapy and interventions and provide unique opportunities for development of new contrast agents.

CT Phantom Evaluation of 67,392 American College of Radiology Accreditation Examinations: Implications for Opportunistic Screening of Osteoporosis Using CT

OBJECTIVE. The purpose of this study was to investigate whether systematic bias in attenuation measurements occurs among CT scanners made by four major manufacturers and the relevance of this bias regarding opportunistic screening for osteoporosis. MATERIALS AND METHODS. Data on attenuation measurement accuracy were acquired using the American College of Radiology (ACR) accreditation phantom and were evaluated in a blinded fashion for four CT manufacturers (8500 accreditation submissions for manufacturer A; 18,575 for manufacturer B; 8278 for manufacturer C; and 32,039 for manufacturer D). The attenuation value for water, acrylic (surrogate for trabecular bone), and Teflon (surrogate for cortical bone; Chemours) materials for an adult abdominal CT technique (120 kV, 240 mA, standard reconstruction algorithm) was used in the analysis. Differences in attenuation value across all manufacturers were assessed using the Kruskal-Wallis test followed by a post hoc test for pairwise comparisons. RESULTS. The mean attenuation value for water ranged from -0.3 to 2.7 HU, with highly significant differences among all manufacturers (p < 0.001). For the trabecular bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 120.9 (SD, 3.5), 124.6 (3.3), 126.9 (4.4), and 123.9 (3.4) HU for manufacturers A, B, C, and D, respectively. For the cortical bone surrogate, differences in attenuation values across all manufacturers were also highly significant (p < 0.001), with mean values of 939.0 (14.2), 874.3 (13.3), 897.6 (11.3), and 912.7 (13.4) HU for manufacturers A, B, C, and D, respectively. CONCLUSION. CT scanners made by different manufacturers show systematic offsets in attenuation measurement when compared with each other. Knowledge of these off-sets is useful for optimizing the accuracy of opportunistic diagnosis of osteoporosis.

Effect of miscentering and low-dose protocols on contrast resolution in computed tomography head examination

BACKGROUND

Unoptimized protocols, including a miscentered position, might affect the outcome of diagnostic in CT examinations. In this study, we investigate the effects of miscentering position during CT head examination on the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR).

METHOD

We simulate the CT head examination using a water phantom with a standard protocol (120 kVp/180 mAs) and a low dose protocol (100 kVp/142 mAs). The table height was adjusted to simulate miscentering by 5 cm from the isocenter, where the height was miscentered superiorly (MCS) at 109, 114, 119, and 124 cm, and miscentered inferiorly (MCI) at 99, 94, 89, and 84 cm. Seven circular regions of interest were used, with one drawn at the center, four at the peripheral area of the phantom, and two at the background area of the image.

RESULTS

For the standard protocol, the mean CNR decreased uniformly as table height increased and significantly differed (p < 0.05) at +20 cm for MCS (435.70 ± 9.39) and -20 cm for MCI (438.91 ± 10.94) from the isocenter. Similarly, significant reductions (p < 0.05) were also noted for SNR for MCS (at +20 cm) and MCI (at -20 cm). For the low dose protocol, both CNR and SNR were significantly reduced (p < 0.05) at table heights of +20 and -20 cm from the isocenter.

CONCLUSION

Miscentering is proven to significantly affect the image quality in both low and standard dose protocols for head CT procedure. This study implies that accurate patient centering is one of the approaches that can improve CT optimization practice.

Reticular pattern around superior mesenteric artery in computed tomography imaging predicting poor prognosis of pancreatic head cancer

BACKGROUND

Some patients with pancreatic ductal adenocarcinoma (PDAC) demonstrate a reticular pattern around the superior mesenteric artery (SMA) in computed tomography scans. This study aimed to clarify the clinical significance of the reticular pattern in pancreatic head cancer.

METHODS

A total of 91 patients with pancreatic head cancer, who underwent upfront pancreaticoduodenectomy between 2004 and 2017, were included. Patients without reticular pattern (Non-group, n = 39); with reticular pattern around SMA (Ret-group, n = 39); and with soft tissue contact (Soft-group, n = 13) were compared.

RESULTS

Median overall survival (OS) of patients in the Ret-group was significantly worse than that in the Non-group (21.3 vs. 57.0 months; P < 0.001) and equivalent to that in the Soft-group. In the multivariate analysis, reticular pattern and high CA19-9 levels were identified as independent predictors of OS. Microscopically, only fibrotic thickenings were identified corresponding to the reticular pattern areas, and no difference in the frequency of early local recurrence was noted between the Non and Ret-groups. Lymphovascular invasion was significantly different between the two groups; furthermore, early distant recurrence was more frequent in the Ret-group.

CONCLUSIONS

The reticular pattern around SMA is an important prognostic factor related to frequent distant recurrence in patients with pancreatic cancer.

Patient centring and scan length: how inaccurate practice impacts on radiation dose in CT colonography (CTC)

OBJECTIVE

The aim of this study was to acknowledge errors in patients positioning in CT colonography (CTC) and their effect in radiation exposure.

MATERIALS AND METHODS

CTC studies of a total of 199 patients coming from two different referral hospitals were retrospectively reviewed. Two parameters have been considered for the analysis: patient position in relation to gantry isocentre and scan length related to the area of interest. CTDI vol and DLP were extracted for each patient. In order to evaluate the estimated effective total dose and the dose to various organs, we used the CT-EXPO^® software version 2.2. This software provides estimates of effective dose and doses to the other various organs.

RESULTS

Average value of the patients' position is found to be below the isocentre for 48 ± 25 mm and 29 ± 27 mm in the prone and supine position. It was observed that the increase in CTDI and DLP values for patients in Group 1, due to the inaccurate positioning, was estimated at about 30% and 20% for prone and supine position, respectively, while in Group 2, a decrease in CTDI and DLP values was estimated at about 16% and 18% for prone and supine position, respectively, due to an average position above isocentre. A dose increase ranging from 4 up to 13% was calculated with increasing the over-scanned region below anal orifice.

CONCLUSION

Radiographers and radiologists need to be aware of dose variation and noise effects on vertical positioning and over-scanning. More accurate training need to be achieved even so when examination protocol varies from general practice.

The effect of vertical centering and scout direction on automatic tube voltage selection in chest CT: a preliminary phantom study on two different CT equipments

Purpose

To determine the effect of patient's vertical off-centering and scout direction on the function of automatic tube voltage selection (ATVS) and tube current modulation (TCM) in chest computed tomography (CT).

Methods

Chest phantom was scanned with Siemens and GE CT systems using three clinical chest CT protocols exploiting ATVS and a fixed 120 kVp chest protocol. The scans were performed at five vertical positions of the phantom (-6 to +6 cm from the scanner isocenter). The effects of scout direction (posterior-to-anterior, anterior-to-posterior, and lateral) and vertical off-centering on the function of ATVS and TCM were studied by examining changes in selected voltage, radiation dose (volume CT dose index, CTDI_vol), and image noise and contrast.

Results

Both scout direction and vertical off-centering affected ATVS. The effect differed between the vendors for the studied geometry, demonstrating differences in technical approaches. The greatest observed increase in CTDI_vol due to off-centering was 91%. Anterior-to-posterior scout produced highest doses at the uppermost table position, whereas posterior-to-anterior scout produced highest doses at the lowermost table position. Dose varied least using lateral scouts. Vertical off-centering impacted image noise and contrast due to the combined effect of ATVS, TCM, structural noise, and bowtie filters.

Conclusions

Patient vertical off-centering and scout direction affected substantially the CTDI_vol and image quality in chest CT examinations. Vertical off-centering caused variation also in the selected tube voltage. The function of ATVS and TCM methods differ significantly between the CT vendors, resulting in differences in CTDI_vol and image noise characteristics.

Population-based opportunistic osteoporosis screening: Validation of a fully automated CT tool for assessing longitudinal BMD changes

METHODS:

The automated BMD tool was retrospectively applied to non-contrast abdominal CT scans in 1603 consecutive asymptomatic adults (mean age, 55.9 years; 770 M/833 F) undergoing longitudinal screening (mean interval, 5.7 years; range, 1.0-12.3 years). The spinal column was automatically segmented, with standardized L1 and L2 anterior trabecular ROI placement. Automated and manual L1 HU values were compared, as were automated supine-prone measures. L1-L2 CT attenuation values were converted to BMD values through a linear regression model. BMD values and changes were assessed according to age and gender.

RESULTS:

Success rate of the automated BMD tool was 99.8 % (four failed cases). Both automated supine vs prone and manual vs automated L1 attenuation measurements showed good agreement. Overall mean annual rate of bone loss was greater in females than males (-2.0% vs -1.0%), but the age-specific rate declined faster in females from age 50 (-2.1%) to age 65 (-0.3%) compared with males (-0.9% to -0.5%). Mean BMD was higher in females than males at age 50 (143.6 vs 135.1  mg cm^-3), but post-menopausal bone loss in females reversed this relationship beyond age 60. By age 70, mean BMD in females and males was 100.8 and 107.7  mg cm^-3 , respectively.

CONCLUSION:

This robust, fully automated CT BMD tool allows for both individualized and population-based assessment. Mean BMD was lower in men than women aged 50-60, but accelerated post-menopausal bone loss in women resulted in lower values beyond age 60.

ADVANCES IN KNOWLEDGE:

This fully automated tool can be applied to routine abdominal CT scans for prospective or retrospective opportunistic BMD assessment, including change over time. Mean BMD was lower in men compared with women aged 50-60 years, but accelerated bone loss in women during this early post-menopausal period resulted in lower BMD values for women beyond age 60.

Dynamic fluence field modulation for miscentered patients in computed tomography

Traditional CT image acquisition uses bowtie filters to reduce dose, x-ray scatter, and detector dynamic range requirements. However, accurate patient centering within the bore of the CT scanner takes time and is often difficult to achieve precisely. Patient miscentering combined with a static bowtie filter can result in significant increases in dose, reconstruction noise, and CT number variations, and consequently raise overall exposure requirements. Approaches to estimate the patient position from scout scans and perform dynamic spatial beam filtration during acquisition are developed and applied in physical experiments on a CT test bench using different beam filtration strategies. While various dynamic beam modulation strategies have been developed, we focus on two approaches: (1) a simple approach using attenuation-based beam modulation using a translating bowtie filter and (2) dynamic beam modulation using multiple aperture devices (MADs)-an emerging beam filtration strategy based on binary filtration of the x-ray beam using variable width slits in a high-density beam blocker. Improved dose utilization and more consistent image performance with respect to an unmodulated baseline (static filter) are demonstrated for miscentered objects and dynamic beam filtration in physical experiments. For a homogeneous object miscentered by 4 cm, the dynamic filter reduced the maximum regional noise and dose penalties (compared with a centered object) from 173% to 16% and 42% to 14%, respectively, for a traditional bowtie, 29% to 8% and 24% to 15%, respectively, for a single MAD, and 275% to 11% and 56% to 18%, respectively, for a dual-MAD filter. The proposed methodology has the potential to relax patient centering requirements within the scanner, reduce setup time, and facilitate additional CT dose reduction.

Dynamic beam filtering for miscentered patients

Purpose

Accurate centering of the patient within the bore of a CT scanner takes time and is often difficult to achieve precisely. Patient miscentering can result in significant dose and image noise penalties with the use of traditional bowtie filters. This work describes a system to dynamically position an x-ray beam filter during image acquisition to enable more consistent image performance and potentially lower dose needed for CT imaging.

Methods

We propose a new approach in which two orthogonal low-dose scout images are used to estimate a parametric model of the object describing its shape, size, and location within the field of view (FOV). This model is then used to compute an optimal filter motion profile by minimizing the variance of the expected detector fluence for each projection. Dynamic filtration was implemented on a cone-beam CT (CBCT) test bench using two different physical filters: 1) an aluminum bowtie and 2) a structured binary filter called a multiple aperture device (MAD). Dynamic filtration performance was compared to a static filter in studies of dose and reconstruction noise as a function of the degree of miscentering of a homogeneous water phantom.

Results

Estimated filter trajectories were found to be largely sinusoidal with an amplitude proportional to the amount of miscentering. Dynamic filtration demonstrated an improved ability to keep the spatial distribution of dose and reconstruction noise at baseline levels across varying levels of miscentering, reducing the maximum noise and dose deviation from 53% to 15% and 42% to 14% respectively for the bowtie filter, and 25% to 8% and 24% to 15% respectively for the MAD filter.

Conclusion

Dynamic positioning of beam filters during acquisition improves dose utilization and image quality over static filters for miscentered patients. Such dynamic filters relax positioning requirements and have the potential to reduce set-up time and lower dose requirements.

Automated image quality assessment for chest CT scans

PURPOSE

Medical image quality needs to be maintained at standards sufficient for effective clinical reading. Automated computer analytic methods may be applied to medical images for quality assessment.

METHODS

For chest CT scans in a lung cancer screening context, an automated quality assessment method is presented that characterizes image noise and image intensity calibration. This is achieved by image measurements in three automatically segmented homogeneous regions of the scan: external air, trachea lumen air, and descending aorta blood. Profiles of CT scanner behavior are also computed.

RESULTS

The method has been evaluated on both phantom and real low-dose chest CT scans and results show that repeatable noise and calibration measures may be realized by automated computer algorithms. Noise and calibration profiles show relevant differences between different scanners and protocols.

CONCLUSIONS

Automated image quality assessment may be useful for quality control for lung cancer screening and may enable performance improvements to automated computer analysis methods.