Computed tomography recent history and future perspectives

Assessing the inter-observer and intra-observer reliability of radiographic measurements for size-specific dose estimates

BACKGROUND

Calculating size-specific dose estimates (SSDEs) requires measurement of the patient's anteroposterior (AP) and lateral thickness based on computed tomography (CT) images. However, these measurements can be subject to variation due to inter-observer and intra-observer differences. This study aimed to investigate the impact of these variations on the accuracy of the calculated SSDE.

METHODS

Four radiographers with 1-10 years of experience were invited to measure the AP and lateral thickness on 30 chest, abdomen, and pelvic CT images. The images were sourced from an internet-based database and anonymized for analysis. The observers were trained to perform the measurements using MicroDicom software and asked to repeat the measurements 1 week later. The study was approved by the institutional review board at Taibah University, and written informed consent was obtained from the observers. Statistical analyses were performed using Python libraries Pingouin (version 0.5.3), Seaborn (version 0.12.2), and Matplotlib (version 3.7.1).

RESULTS

The study revealed excellent inter-observer agreement for the calculated effective diameter and AP thickness measurements, with Intraclass correlation coefficients (ICC) values of 0.95 and 0.96, respectively. The agreement for lateral thickness measurements was lower, with an ICC value of 0.89. The second round of measurements yielded nearly the same levels of inter-observer agreement, with ICC values of 0.97 for the effective diameter, 1.0 for AP thickness, and 0.88 for lateral thickness. When the consistency of the observer was examined, excellent consistency was found for the calculated effective diameter, with ICC values ranging from 0.91 to 1.0 for all observers. This was observed despite the lower consistency in the lateral thickness measurements, which had ICC values ranging from 0.78 to 1.0.

CONCLUSIONS

The study's findings suggest that the measurements required for calculating SSDEs are robust to inter-observer and intra-observer differences. This is important for the clinical use of SSDEs to set diagnostic reference levels for CT scans.

Artificial Intelligence in Pancreatic Image Analysis: A Review

Pancreatic cancer is a highly lethal disease with a poor prognosis. Its early diagnosis and accurate treatment mainly rely on medical imaging, so accurate medical image analysis is especially vital for pancreatic cancer patients. However, medical image analysis of pancreatic cancer is facing challenges due to ambiguous symptoms, high misdiagnosis rates, and significant financial costs. Artificial intelligence (AI) offers a promising solution by relieving medical personnel's workload, improving clinical decision-making, and reducing patient costs. This study focuses on AI applications such as segmentation, classification, object detection, and prognosis prediction across five types of medical imaging: CT, MRI, EUS, PET, and pathological images, as well as integrating these imaging modalities to boost diagnostic accuracy and treatment efficiency. In addition, this study discusses current hot topics and future directions aimed at overcoming the challenges in AI-enabled automated pancreatic cancer diagnosis algorithms.

Establishing a Foundation for the In Vivo Visualization of Intravascular Blood with Photon-Counting Technology in Spectral Imaging in Cranial CT

BACKGROUND

Advances in computed tomography (CT) technology, particularly photon-counting CT (PCCT), are reshaping the possibilities for medical imaging. PCCT in spectral imaging enables the high-resolution visualization of tissues with material-specific accuracy. This study aims to establish a foundational approach for the in vivo visualization of intracranial blood using PCCT, focusing on non-enhanced imaging techniques and spectral imaging capabilities.

METHODS

We employed photon-counting detector within a spectral CT framework to differentiate between venous and arterial intracranial blood. Our analysis included not only monoenergetic +67 keV reconstructions, but also images from virtual non-contrast and iodine phases, enabling detailed assessments of blood's characteristics without the use of contrast agents.

RESULTS

Our findings demonstrate the ability of PCCT to provide clear and distinct visualizations of intracranial vascular structures. We quantified the signal-to-noise ratio across different imaging phases and found consistent enhancements in image clarity, particularly in the detection and differentiation of arterial and venous blood.

CONCLUSION

PCCT offers a robust platform for the non-invasive and detailed visualization of intravascular intracranial blood. With its superior resolution and specific imaging capabilities, PCCT lays the groundwork for advancing clinical applications and research, notably in the diagnosis and management of intracranial disorders. This technology promises to improve diagnostic accuracy by enabling more precise imaging assessments.

Computed tomography (CT) scanning to visualize eye formation and internal structure in Grevé cheese

The Grevé cheese, a semi-hard Swedish cheese, is well-known for its characteristic flavor and shape of eye formation. The size and distribution of the eyes play a crucial role for the sensory attributes, aesthetic value and quality of the cheese. This article focuses on investigating the feasibility of using computed tomography (CT) scanning as a non-destructive tool to observe early-stage eye formation in Grevé cheese within an industrial trial. It is crucial to achieve a perfect combination of small and big sized eyes, evenly distributed within the cheese wheel, without having cracks/splits for optimal quality. Such variations could be visualized using CT-scanning of cheeses at a young and mature stage by providing high-resolution, three-dimensional CT-scanning images of the cheese's internal structure, without the need for physical dissection. Further, the distribution of eyes, their shape and number, could be visualized and compared for the same cheese scanned at young and mature stages. Thus, the importance of monitoring eye formation through non-destructive techniques is emphasized to ensure consistent product quality.

Assessing nasal airway resistance and symmetry: An approach to global perspective through computational fluid dynamics

This study aimed to explore the variability in nasal airflow patterns among different sexes and populations using computational fluid dynamics (CFD). We focused on evaluating the universality and applicability of dimensionless parameters R (bilateral nasal resistance) and ϕ (nasal flow asymmetry), initially established in a Caucasian Spanish cohort, across a broader spectrum of human populations to assess normal breathing function in healthy airways. In this retrospective study, CT scans from Cambodia (20 males, 20 females), Russia (20 males, 18 females), and Spain (19 males, 19 females) were analyzed. A standardized CFD workflow was implemented to calculate R-ϕ parameters from these scans. Statistical analyses were conducted to assess and compare these parameters across different sexes and populations, emphasizing their distribution and variances. Our results indicated no significant sex-based differences in the R parameter across the populations. However, moderate sexual dimorphism in the ϕ parameter was observed in the Cambodian group. Notably, no geographical differences were found in either R or ϕ parameters, suggesting consistent nasal airflow characteristics across the diverse human groups studied. The study also emphasized the importance of using dimensionless variables to effectively analyze the relationships between form and function in nasal airflow. The observed consistency of R-ϕ parameters across various populations highlights their potential as reliable indicators in both medical practice and further CFD research, particularly in diverse human populations. Our findings suggest the potential applicability of dimensionless CFD parameters in analyzing nasal airflow, highlighting their utility across diverse demographic and geographic contexts. This research advances our understanding of nasal airflow dynamics and underscores the need for additional studies to validate these parameters in broader population cohorts. The approach of employing dimensionless parameters paves the way for future research that eliminates confounding size effects, enabling more accurate comparisons across different populations and sexes. The implications of this study are significant for the advancement of personalized medicine and the development of diagnostic tools that accommodate individual variations in nasal airflow.

Photon-counting CT: technical features and clinical impact on abdominal imaging

Photon-counting CT has a completely different detector mechanism than conventional energy-integrating CT. In the photon-counting detector, X-rays are directly converted into electrons and received as electrical signals. Photon-counting CT provides virtual monochromatic images with a high contrast-to-noise ratio for abdominal CT imaging and may improve the ability to visualize small or low-contrast lesions. In addition, photon-counting CT may offer the possibility of reducing radiation dose. This review provides an overview of the actual clinical operation of photon-counting CT and its diagnostic utility in abdominal imaging. We also describe the clinical implications of photon-counting CT including imaging of hepatocellular carcinoma, liver metastases, hepatic steatosis, pancreatic cancer, intraductal mucinous neoplasm of the pancreas, and thrombus.

Cardiac CT: Competition, complimentary or confounder

Coronary CT angiography (CCTA) has been gradually adopted into clinical practice over the last two decades. CCTA has high diagnostic accuracy, prognostic value, and unique features such as assessment of plaque composition. CCTA-derived functional assessment techniques such as fractional flow reserve and CT perfusion are also available and can increase the diagnostic specificity of the modality. These properties propound CCTA as a competitor of functional testing in diagnosis of obstructive CAD, however, utilizing CCTA in a concomitant fashion to potentiate the performance of the latter can lead to better patient care and may provide more accurate prognostic information. Although multiple diagnostic challenges such as evaluation of calcified segments, stents, and small distal vessels still exist, the technologic developments in hardware as well as growing incorporation of artificial intelligence to daily practice are all set to augment the diagnostic and prognostic role of CCTA in cardiovascular disorders.

Recanalization status and temporal evolution of early ischemic changes following stroke thrombectomy

INTRODUCTION

Present-day computer tomography (CT) scanners have excellent spatial resolution and signal-to-noise ratio and are instrumental detecting early ischemic changes (EIC) in brain. We assessed the temporal changes of EIC based on the recanalization status after thrombectomy.

PATIENTS AND METHODS

The cohort comprises consecutive patients with acute ischemic stroke in anterior circulation treated with thrombectomy in tertiary referral hospital. All baseline and follow-up scans were screened for any ischemic changes and further classified using Alberta Stroke Program Early CT Score (ASPECTS). Generalized linear mixed models were used to analyze the impact of recanalization status using modified Thrombolysis in Cerebral Infarction (mTICI) on temporal evolution of ischemic changes.

RESULTS

We included 614 patients with ICA, M1, or M2 occlusions. Median ASPECTS score was 9 (IQR 7-10) at baseline and 7 (5-8) at approximately 24 h. mTICI 3 was achieved in 207 (33.8%), 2B 241 (39.3%), 2A in 77 (12.6%), and 0-1 in 88 (14.3%) patients. Compared to patients with mTICI 3, those with mTICI 0-1 and 2A had less favorable temporal changes of ASPECTS (p < 0.001). Effect of recanalization was noted in the cortical regions of ICA/M1 patients, but not in their deep structures or patients with M2 occlusions. All ischemic changes detected at baseline were also present at all follow-up images, regardless of the recanalization status.

CONCLUSIONS

Temporal evolution of the ischemic changes and ASPECTS are related to the success of the recanalization therapy in cortical regions of ICA/M1 patients, but not in their deep brain structures or M2 patients. In none of the patients did EIC revert in any brain region after successful recanalization.

Approaches, advantages, and challenges to photon counting detector and multi-energy CT

Photon counting detector CT (PCD-CT) is the newest major development in CT technology and has been commercially available since 2021. It offers major technological advantages over current standard-of-care energy integrating detector CT (EID-CT) including improved spatial resolution, improved iodine contrast to noise ratio, multi-energy imaging, and reduced noise. This article serves as a foundational basis to the technical approaches and concepts of PCD-CT technology with primary emphasis on detector technology in direct comparison to EID-CT. The article also addresses current technological challenges to PCD-CT with particular attention to cross talk and its causes (e.g., Compton scattering, fluorescence, charge sharing, K-escape) as well as pile-up.

Improved small vessel visibility in diabetic foot arteriography using dual-energy CT

AIM

To test the feasibility and performance of dual-energy computed tomography (DECT) in foot arteriography of diabetic patients, where contrast medium is largely reduced within the small vessels.

MATERIALS AND METHODS

A total of 50 diabetic patients were enrolled prospectively, where DECT was acquired immediately after the CT angiography (CTA, group A) of the lower extremity. Two images were derived from the DECT data, one optimal virtual monochromatic image (VMI, group B) and one fusion image (group C), both of which were compared against the CTA image for visualising the foot arteries. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were evaluated. The arterial course and contrast were graded each using a five-point scale. The clarity of small vessel depiction was quantified by comparing the number of plantar metatarsal arteries found in the maximum intensity projection image.

RESULTS

The median CNRs and SNRs obtained in group B were approximately 45% and 20% higher than those in groups A and C, respectively (p<0.05). Group B also received higher subjective scores on the posterior tibial artery and the foot arteries (all >3) than groups A and C. The number of visible branches of the plantar metatarsal arteries was found to be substantially higher (p<0.05) in group B (median=6) than in groups A (median=2) and C (median=4).

CONCLUSION

DECT was found to be superior to conventional CTA in foot arteriography, and beyond the lower extremity, it might be a general favourable solution for imaging regions with small vessels and reduced contrast medium.

Possible improvements in effective fill factor using X-ray fluorescent interpixel reflectors

BACKGROUND

The spatial resolution of energy-integrating diagnostic CT scanners is limited by interpixel reflectors on the detector, which optically isolate pixels but create dead space. Because the width of the reflector cannot easily be decreased, fill factor diminishes as resolution increases.

PURPOSE

We propose loading (or mixing) a high-Z element into the reflectors, causing the reflectors to be X-ray fluorescent. Re-emitted characteristic X-rays could be detected in adjacent pixels, increasing the effective fill factor and compensating for fill factor loss with higher-resolution detectors. The purpose of this work is to understand the physical principles of this approach and to analyze its effectiveness using Monte Carlo simulations.

METHODS

Detector pixels were modeled using the GEANT4 Monte Carlo package. The width of the reflector was kept constant at 0.1 mm throughout, and we considered pixel pitches between 0.5 and 1 mm. The pixelated scintillator material was gadolinium oxysulfide, 3 mm thick. The baseline reflector material was chosen to be acrylic, and varying concentrations of a high-Z element were loaded into the material. We assumed that the optical characteristics of pixels were ideal (no absorption within pixels, perfect reflection at boundaries). The detector was irradiated uniformly with 10,000 X-ray photons to estimate its spectral response. The figure of merit was the variance of the detector signal at zero frequency normalized to that of an ideal single-bin photon-counting detector with 100% fill factor. Sensitivity analyses were conducted to understand the effect of varying the high-Z element concentration and the spectrum.

RESULTS

Initial simulations suggested that a k-edge near 50 keV would be ideal. Gd was therefore selected as the high-Z material. The relative variances for a conventional energy integrating detector without Gd at 1 mm pixel pitch (81% fill factor) and 0.5 mm pixel pitch (64% fill factor) were 1.38 and 1.74, compared to 1.00 for an ideal photon counting detector, implying a 26% variance penalty for 0.5 mm pitch. When 1 g/cm3 Gd was loaded into the interpixel reflector, the relative variance improved to 1.27 and 1.43, respectively, implying that the variance penalty for including Gd together with 0.5 mm pitch is only 4%. Performance was nearly maximized at 1.0 g/cm3 of Gd, but a concentration of 0.5 g/cm3 of Gd showed most of the benefit. Improvements depend weakly on kV, with lower kV associated with higher improvements. An external anti-scatter grid was not modeled in our simulations and would reduce the expected benefit, depending greatly on the pitch and dimensionality of the anti-scatter grid.

CONCLUSIONS

The losses in fill factor associated with smaller pixel pitch can be reduced if Gd or a similar element could be loaded into the interpixel reflector. These improvements in noise efficiency are yet to be verified experimentally.

A look at radiation detectors and their applications in medical imaging

The effectiveness and precision of disease diagnosis and treatment have increased, thanks to developments in clinical imaging over the past few decades. Science is developing and progressing steadily in imaging modalities, and effective outcomes are starting to show up as a result of the shorter scanning periods needed as well as the higher-resolution images generated. The choice of one clinical device over another is influenced by technical disparities among the equipment, such as detection medium, shorter scan time, patient comfort, cost-effectiveness, accessibility, greater sensitivity and specificity, and spatial resolution. Lately, computational algorithms, artificial intelligence (AI), in particular, have been incorporated with diagnostic and treatment techniques, including imaging systems. AI is a discipline comprised of multiple computational and mathematical models. Its applications aided in manipulating sophisticated data in imaging processes and increased imaging tests' accuracy and precision during diagnosis. Computed tomography (CT), positron emission tomography (PET), and Single Photon Emission Computed Tomography (SPECT) along with their corresponding radiation detectors have been reviewed in this study. This review will provide an in-depth explanation of the above-mentioned imaging modalities as well as the radiation detectors that are their essential components. From the early development of these medical instruments till now, various modifications and improvements have been done and more is yet to be established for better performance which calls for a necessity to capture the available information and record the gaps to be filled for better future advances.

Discordance between GCIG CA-125 progression and RECIST progression in the CALYPSO trial of patients with platinum-sensitive recurrent ovarian cancer

BACKGROUND

CA-125 alone is widely used to diagnose progressive disease (PD) in platinum-sensitive recurrent ovarian cancer (PSROC) on chemotherapy. However, there are increasing concerns regarding its accuracy. We assessed concordance between progression defined by CA-125 and RECIST using data from the CALYPSO trial.

METHODS

We computed concordance rates for PD by CA-125 and RECIST to determine the positive (PPV) and negative predictive values (NPV).

RESULTS

Of 769 (79%) evaluable participants, 387 had CA-125 PD, where only 276 had concordant RECIST PD (PPV 71%, 95% CI 67-76%). For 382 without CA-125 PD, 255 had RECIST PD but 127 did not (NPV 33%, 95% CI 29-38). There were significant differences in NPV according to baseline CA-125 (≤100 vs >100: 42% vs 25%, P < 0.001); non-measurable vs measurable disease (51% vs 26%, P < 0.001); and platinum-free-interval (>12 vs 6-12 months: 41% vs 14%, P < 0.001). We observed falling CA-125 levels in 78% of patients with RECIST PD and CA-125 non-PD.

CONCLUSION

Approximately 2 in 3 women with PSROC have RECIST PD but not CA-125 PD by GCIG criteria. Monitoring CA-125 levels alone is not reliable for detecting PD. Further research is required to investigate the survival impact of local therapy in radiological detected early asymptomatic PD.

Dose-efficiency quantification of computed tomography systems using a model-observer

BACKGROUND

Recent advances in computed tomography (CT) technology have considerably improved the quality of CT images and reduced radiation exposure in patients. At present, however, there is no generally accepted figure of merit (FOM) for comparing the dose efficiencies of CT systems.

PURPOSE

(i) To establish an FOM that characterizes the quality of CT images in relation to the radiation dose by means of a mathematical model observer and (ii) to evaluate the new FOM on different CT systems and image reconstruction algorithms.

METHODS

Images of a homogeneous phantom with four low-contrast inserts were acquired using three different CT systems at three dose levels and a representative protocol for CT imaging of low-contrast objects in the abdomen. The images were reconstructed using filtered-back projection and iterative algorithms. A channelized hotelling observer with difference-of-Gaussian channels was applied to compute the detectability (d ' $d^{\prime}$ ). This was done for each insert and each of the considered imaging conditions from square regions of interest (ROIs) that were (semi-)automatically centered on the inserts. The estimated detectabilities (d ' $d^{\prime}$ ) were averaged in the first step over the three dose levels (⟨ d ' ⟩ $\langle {d^{\prime}} \rangle $ ), and subsequently over the four contrast inserts (⟨ d ' ⟩ w ${\langle {d^{\prime}} \rangle _{\rm{w}}}$ ). All calculation steps included a dedicated assessment of the related uncertainties following accepted metrological guidelines.

RESULTS

The determined detectabilities (d ' $d^{\prime}$ ) varied considerably with the contrast and diameter of the four inserts, as well as with the radiation doses and reconstruction algorithms used for image generation (d ' $d^{\prime}\;$ = 1.3-5.5). Thus, the specification of a single detectability as an FOM is not well suited for comprehensively characterizing the dose efficiency of a CT system. A more comprehensive and robust characterization was provided by the averaged detectabilities⟨ d ' ⟩ $\langle {d^{\prime}} \rangle $ and, in particular,⟨ d ' ⟩ w ${\langle {d^{\prime}} \rangle _{\rm{w}}}$ . Our analysis reveals that the model observer analysis is very sensitive to the exact position of the ROIs.

CONCLUSIONS

The presented automatable software approach yielded with the weighted detectability⟨ d ' ⟩ w ${\langle {d^{\prime}} \rangle _{\rm{w}}}$ an objective FOM to benchmark different CT systems and reconstruction algorithms in a robust and reliable manner. An essential advantage of the proposed model-observer approach is that uncertainties in the FOM can be provided, which is an indispensable prerequisite for type testing.

A prospective study comparing the quality of coronary computed tomography angiography images from photon counting and energy integrating detector systems

BACKGROUND

As guidelines endorse the use of computed tomography (CT) for examining coronary artery disease (CAD), it is important to compare the advantages and disadvantages of the novel photon counting detector CT (PCD-CT) technology with the established energy integrating detector CT (EID-CT).

PURPOSE

To compare the image quality of coronary computed tomography angiography (CCTA) and the Agatston scores (AS) derived from EID-CT and PCD-CT.

MATERIAL AND METHODS

In this prospective observational study, 28 patients underwent clinical calcium score and CCTA scans on an EID-CT and a PCD-CT scanner. CCTA images were qualitatively analyzed by five observers using visual grading characteristics. The correlation and agreement of the AS were assessed using Spearman's rank correlation and Bland-Altman plots.

RESULTS

This qualitative analyses demonstrated a high fraction of "good" or "excellent" ratings for the image criteria in both CT systems. The sharpness of the distal lumen and image quality regarding motion artifacts were rated significantly higher for EID-CT (P < 0.05). However, the sharpness of coronary calcification was rated significantly higher for PCD-CT (P < 0.05). Spearman's rank correlation and Bland-Altman plots showed good correlation (P = 0.95) and agreement regarding the AS between EID-CT and PCD-CT.

CONCLUSION

Both CT systems exhibited high CCTA image quality. The sharpness of calcifications was rated significantly higher for PCD-CT. A good correlation was observed between the AS derived from the two systems.

Reducing radiation dose for NN-based COVID-19 detection in helical chest CT using real-time monitored reconstruction

Computed tomography is a powerful tool for medical examination, which plays a particularly important role in the investigation of acute diseases, such as COVID-19. A growing concern in relation to CT scans is the radiation to which the patients are exposed, and a lot of research is dedicated to methods and approaches to how to reduce the radiation dose in X-ray CT studies. In this paper, we propose a novel scanning protocol based on real-time monitored reconstruction for a helical chest CT using a pre-trained neural network model for COVID-19 detection as an expert. In a simulated study, for the first time, we proposed using per-slice stopping rules based on the COVID-19 detection neural network output to reduce the frequency of projection acquisition for portions of the scanning process. The proposed method allows reducing the total number of X-ray projections necessary for COVID-19 detection, and thus reducing the radiation dose, without a significant decrease in the prediction accuracy. The proposed protocol was evaluated on 163 patients from the COVID-CTset dataset, providing a mean dose reduction of 15.1% while the mean decrease in prediction accuracy amounted to only 1.9% achieving a Pareto improvement over a fixed protocol.

Volumetric computed tomography with carbon nanotube X-ray source array for improved image quality and accuracy

Cone beam computed tomography (CBCT) is widely used in medical and dental imaging. Compared to a multidetector CT, it provides volumetric images with high isotropic resolution at a reduced radiation dose, cost and footprint without the need for patient translation. The current CBCT has several intrinsic limitations including reduced soft tissue contrast, inaccurate quantification of X-ray attenuation, image distortions and artefacts, which have limited its clinical applications primarily to imaging hard tissues and made quantitative analysis challenging. Here we report a multisource CBCT (ms-CBCT) which overcomes the short-comings of the conventional CBCT by using multiple narrowly collimated and rapidly scanning X-ray beams from a carbon nanotube field emission source array. Phantom imaging studies show that, the ms-CBCT increases the accuracy of the Hounsfield unit values by 60%, eliminates the cone beam artefacts, extends the axial coverage, and improves the soft tissue contrast-to-noise ratio by 30-50%, compared to the CBCT configuration.

Photon Counting CT: Technical Principles, Clinical Applications, and Future Prospects

Photon-counting computed tomography (PCCT) is a new technique that utilizes photon-counting detectors to convert individual X-ray photons directly into an electrical signal, which can achieve higher spatial resolution, improved iodine signal, radiation dose reduction, artifact reduction, and multienergy imaging. This review introduces the technical principles of PCCT, and summarizes its first-in-human experience and current applications in clinical settings, and discusses the future prospects of PCCT.

Number of computed tomography scanners and regional disparities based on population and medical resources in Japan

This study aimed to discover the associations between the number of computed tomography (CT) scanners and the population, as well as number of medical resources to identify regional disparities in Japan. The number of CT scanners was tabulated for each detector row of CT scanners for hospitals and clinics in each prefecture. The number of CT scanners, patients, medical doctors, radiological technologists, facilities, and beds per 100,000 population was compared. Additionally, the number of hospitals with ≥ 200 beds and multidetector-row CT scanners with ≥ 64 rows were tabulated, and their ratios were calculated. Medical institutions in Japan have installed 14,595 scanners. CT scanners per 100,000 population were the highest in Kochi Prefecture, although the number of CT scanners in hospitals was the highest in Tokyo Prefecture. Multivariate analysis revealed the number of radiological technologists (β coefficient: 0.49; P = 0.03), facilities (β coefficient: 0.12; P < 0.01) and beds (β coefficient: 0.46; P < 0.01) as independent factors for the number of CT scanners. Prefectures with a high proportion of hospitals with ≥ 200 beds also had a relatively high proportion of CT scanners with ≥ 64 rows (P < 0.01). Our survey revealed an association between regional disparities in the number of CT scanners in Japan, the population, and number of medical resources. A positive correlation was found between hospital size and number of CT scanners with ≥ 64 rows.

Generalized-equiangular geometry CT: Concept and shift-invariant FBP algorithms

BACKGROUND

With advanced x-ray source and detector technologies being continuously developed, non-traditional CT geometries have been widely explored. Generalized-Equiangular Geometry CT (GEGCT) architecture, in which an x-ray source might be positioned radially far away from the focus of arced detector array that is equiangularly spaced, is of importance in many novel CT systems and designs.

PURPOSE

GEGCT, unfortunately, has no theoretically exact and shift-invariant analytical image reconstruction algorithm in general. In this study, to obtain fast and accurate reconstruction from GEGCT and to promote its system design and optimization, an in-depth investigation on a group of approximate Filtered Back-Projection (FBP) algorithms with a variety of weighting strategies has been conducted.

METHODS

The architecture of GEGCT is first presented and characterized by using a normalized-radial-offset distance (NROD). Next, shift-invariant weighted FBP-type algorithms are derived in a unified framework, with pre-filtering, filtering, and post-filtering weights, for both fixed and dynamic NROD configurations. Three viable weighting strategies are then presented including a classic one developed by Besson in the literature and two new ones generated from a curvature fitting and from an empirical formula, where all of the three weights can be expressed as certain functions of NROD. After that, an analysis of reconstruction accuracy is conducted with a wide range of NROD. Finally, the weighted FBP algorithm for GEGCT is extended to a three-dimensional form in the case of cone-beam scan with a cylindrical detector array.

RESULTS

Theoretical analysis and numerical study show that weights in the shift-invariant FBP algorithms can guarantee highly accurate reconstruction for GEGCT. A simulation of Shepp-Logan phantom and a GEGCT scan of lung mimicked by using a clinical lung CT dataset both demonstrate that FBP reconstructions with Besson and polynomial weights can achieve excellent image quality, with Peak Signal to Noise Ratio and Structural Similarity being at the same level as that from the standard equiangular fan-beam CT scan. Reconstruction of a cylinder object with multiple contrasts from simulated GEGCT scan with dynamic NROD is also highly consistent with fixed ones when using the Besson and polynomial weights, with root mean square error less than 7 hounsfield units, demonstrating the robustness and flexibility of the presented FBP algorithms. In terms of resolution, the direct FBP methods for GEGCT could achieve 1.35 lp/mm of spatial resolution at 10% modulation transfer functions point, higher than that of the rebinning method which can only reach 1.14 lp/mm. Moreover, 3D reconstructions of a disc phantom reveal that a greater value of NROD for GEGCT will bring less cone beam artifacts as expected.

CONCLUSIONS

We propose the concept of GEGCT and investigate the feasibility of using shift-invariant weighted FBP-type algorithms for reconstruction from GEGCT data without rebinning. A comprehensive analysis and phantom studies have been conducted to validate the effectiveness of proposed weighting strategies in a wide range of NROD for GEGCT with fixed and dynamic NROD.

Effects of convolution filter with beam hardening correction on computed tomography image quality

PURPOSE

To quantify the effects of convolution filters (FC) with beam hardening correction (BHC) compared to FC without BHC on the computed tomography (CT) image quality.

METHODS

This study was conducted on a Canon® Aquilion Lightning scanner. The exposure protocol includes acquisitions at 120 and 100 kVp. Sixteen FCs (8 with and 8 without BHC) were investigated using a Catphan®504 phantom. Uniformity, slice thickness, spatial resolution, Hounsfield unit and noise were analysed using the SPICE-CT ImageJ plugin and the noise power spectrum was analysed using the Imquest software.

RESULTS

It was observed that the BHC did not significantly influence the uniformity, slice thickness, noise and noise power spectrum. Comparisons of 10% MTF between FC01 and FC11 showed relative differences of -29% and -5% at 120 and 100 kVp, respectively, while those between FC09 and FC19 were -55% and -25%. The Hounsfield unit of the Catphan's region of highest electron density was reduced by -7.29% at 120 kVp for FC with BHC. In both cases (FC with and without BHC), the noise values agreed with CT operating manual. At 120 kVp, FC11 and FC09 presented the maximum and minimum noise values, respectively.

CONCLUSION

In CT procedures that quantitatively evaluate the bone or calcium Hounsfield unit, FC with BHC should be avoided due to its effects on Hounsfield units, in special at higher voltage, such as 120 kVp.

Radiopaque Iodosilane-Coated Lipid Hybrid Nanoparticle Contrast Agent for Dual-Modality Ultrasound and X-ray Bioimaging

Here, we report the synthesis of robust hybrid iodinated silica-lipid nanoemulsions (HSLNEs) for use as a contrast agent for ultrasound and X-ray applications. We engineered iodinated silica nanoparticles (SNPs), lipid nanoemulsions, and a series of HSLNEs by a low-energy spontaneous nanoemulsification process. The formation of a silica shell requires sonication to hydrolyze and polymerize/condensate the iodomethyltrimethoxysilane at the oil/water interface of the nanoemulsion droplets. The resulting nanoemulsions (NEs) exhibited a homogeneous spherical morphology under transmission electron microscopy. The particles had diameters ranging from 20 to 120 nm with both negative and positive surface charges in the absence and presence of cetyltrimethylammonium bromide (CTAB), respectively. Unlike CTAB-coated nanoformulations, the CTAB-free NEs showed excellent biocompatibility in murine RAW macrophages and human U87-MG cell lines in vitro. The maximum tolerated dose assessment was evaluated to verify their safety profiles in vivo. In vitro X-ray and ultrasound imaging and in vivo computed tomography were used to monitor both iodinated SNPs and HSLNEs, validating their significant contrast-enhancing properties and suggesting their potential as dual-modality clinical agents in the future.

Unified fast reconstruction algorithm for conventional, phase-contrast, and diffraction tomography

A unified method for three-dimensional reconstruction of objects from transmission images collected at multiple illumination directions is described. The method may be applicable to experimental conditions relevant to absorption-based, phase-contrast, or diffraction imaging using x rays, electrons, and other forms of penetrating radiation or matter waves. Both the phase retrieval (also known as contrast transfer function correction) and the effect of Ewald sphere curvature (in the cases with a shallow depth of field and significant in-object diffraction) are incorporated in the proposed algorithm and can be taken into account. Multiple scattering is not treated explicitly but can be mitigated as a result of angular averaging that constitutes an essential feature of the method. The corresponding numerical algorithm is based on three-dimensional gridding which allows for fast computational implementation, including a straightforward parallelization. The algorithm can be used with any scanning geometry involving plane-wave illumination. A software code implementing the proposed algorithm has been developed, tested on simulated and experimental image data, and made publicly available.

Imaging in translational cancer research

This review is aimed at presenting some of the recent developments in translational cancer imaging research, with a focus on novel, recently established, or soon to be established cross-sectional imaging techniques for computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET) imaging, including computational investigations based on machine-learning techniques.

Clinical Application of Spiral CT Reconstruction Imaging in Patients with Tracheal Stenosis before Anesthesia

In order to solve the problem of CT reconstruction imaging, this paper presents a study on the clinical application of preanesthesia in patients with tracheal stenosis. Patients with tracheal stenosis and multislice spiral CT virtual endoscopy (CTVE) were diagnosed, and their application effects were analyzed. Methods. 60 patients with tracheal stenosis were selected for clinical observation. The patients were given tracheal stenosis examination and multislice spiral CT virtual endoscopy. The examination results of the two groups were compared and analyzed by statistical methods. Results. There was no significant difference in the detection rate, sensitivity, accuracy, and specificity between the two groups ( $P>0.05$ ). Conclusion. Multislice spiral CT virtual endoscopy combined with a fiberoptic bronchoscope for clinical diagnosis of tracheal stenosis can complement each other. Combined use can effectively improve the detection consistency, and is safe and reliable. It can be used as an effective means for the diagnosis of tracheal stenosis.

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.

From EMI to AI: a brief history of commercial CT reconstruction algorithms

Computed tomography was one of the first imaging modalities to require a computerized solution of an inverse problem to produce a useful image from the data acquired by the sensor hardware. The computerized solutions, which are known as image reconstruction algorithms, have thus been a critical component of every CT scanner ever sold. We review the history of commercially deployed CT reconstruction algorithms and consider the forces that led, at various points, both to innovation and to convergence around certain broadly useful algorithms. The forces include the emergence of new hardware capabilities, competitive pressures, the availability of computational power, and regulatory considerations. We consider four major historical periods and turning points. The original EMI scanner was developed with an iterative reconstruction algorithm, but an explosion of innovation coupled with rediscovery of an older literature led to the development of alternative algorithms throughout the early 1970s. Most CT vendors quickly converged on the use of the filtered back-projection (FBP) algorithm, albeit layered with a variety of proprietary corrections in both projection data and image domains to improve image quality. Innovations such as helical scanning and multi-row detectors were both enabled by and drove the development of additional applications of FBP in the 1990s and 2000s. Finally, the last two decades have seen a return of iterative reconstruction and the introduction of artificial intelligence approaches that benefit from increased computational power to reduce radiation dose and improve image quality.

Special Section Guest Editorial: Computed tomography (CT) at 50 years

Guest editors Patrick La Riviere, Rebecca Fahrig, and Norbert Pelc introduce the JMI Special Section Celebrating X-Ray Computed Tomography at 50.

How CT happened: the early development of medical computed tomography

As we arrive at the 50th anniversary of the first computed tomography (CT) scan of a live patient, we take this opportunity to revisit the history of early CT development. It is not an exaggeration to say that the invention of CT may represent the greatest revolution in medical imaging since the discovery of x-rays. We cover events over a period of about two decades that started with the realization that accurate cross-sectional soft-tissue detail is possible and could be a significant advance. We describe in some detail the development of the first CT system and then the rapid technical advances during the following years that included the entry of many companies into the field and the circumstances that led many of those entrants to exit the field. Rather than focusing on the specific technical details (which can be found elsewhere), we include stories and events in the hope that broader lessons can be learned. As the first x-ray-based digital imaging modality, CT brought into common use an exceptional tool that benefits countless patients every day. It also introduced dramatic changes to biomedical imaging as a field that continues to influence progress to this day.