Quality assurance in surgical trials of arteriovenous grafts for haemodialysis: A systematic review, a narrative exploration and expert recommendations.

BACKGROUND: Introducing new procedures and challenging established paradigms requires well-designed randomised controlled trials (RCT). However, RCT in surgery present unique challenges with much of treatment tailored to the individual patient circumstances, refined by experience and limited by organisational factors. There has been considerable debate over the outcomes of arteriovenous grafts (AVG) compared to AVF, but any differences may reflect differing practice and potential variability. It is essential, therefore, when considering an RCT of a novel surgical procedure or device that quality assurance (QA) is defined for both the new approach and the comparator. The aim of this systematic review was to evaluate the QA standards performed in RCT of AVG using a multi-national, multi-disciplinary approach and propose an approach for future RCT. METHOD: The methods of this have been previously registered (PROSPERO: CRD420234284280) and published. In summary, a four-stage review was performed: identification of RCT of AVG, initial review, multidisciplinary appraisal of QA methods and reconciliation. QA measures were sought in four areas - generic, credentialing, standardisation and monitoring, with data abstracted by a multi-national, multi-speciality review body. RESULTS: QA in RCT involving AVG in all four domains is highly variable, often sub-optimally described and has not improved over the past three decades. Few RCT established or defined a pre-RCT level of experience, none documented a pre-trial education programme, or had minimal standards of peri-operative management, no study had a defined pre-trial monitoring programme, and none assessed technical performance. CONCLUSION: QA in RCT is a relatively new area that is expanding to ensure evidence is reliable and reproducible. This review demonstrates that QA has not previously been detailed, but can be measured in surgical RCT of vascular access, and that a four-domain approach can easily be implemented into future RCT.

Quality assurance in surgical trials of arteriovenous grafts for haemodialysis: protocol for a systematic review.

INTRODUCTION: Decisions regarding the optimal vascular access for haemodialysis patients are becoming increasingly complex, and the provision of vascular access is open to variations in systems of care as well as surgical experience and practice. Two main surgical options are recognised: arteriovenous fistula and arteriovenous graft (AVG). All recommendations regarding AVG are based on a limited number of randomised controlled trials (RCTs). It is essential that when considering an RCT of a surgical procedure, an appropriate definition of quality assurance (QA) is made for both the new approach and the comparator, otherwise replication of results or implementation into clinical practice may differ from published results. The aim of this systematic review will be to assess the methodological quality of RCT involving AVG, and the QA measures implemented in delivering interventions in these trials. METHODS AND ANALYSIS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines will be followed. A systematic search will be performed of the MEDLINE, Embase and Cochrane databases to identify relevant literature. Studies will be selected by title and abstract review, followed by a full-text review using inclusion and exclusion criteria. Data collected will pertain to generic measures of QA, credentialing of investigators, procedural standardisation and performance monitoring. Trial methodology will be compared against a standardised template developed by a multinational, multispecialty review body with experience in vascular access. A narrative approach will be taken to synthesise and report data. ETHICS AND DISSEMINATION: Ethical approval is not required as it is a protocol for a systematic review. Findings will be disseminated through peer-reviewed publications and conference presentations, with the ultimate aim of providing recommendations for future RCT of AVG design.

Recruitment into randomised trials of arteriovenous grafts: A systematic review.

Although randomised controlled trials (RCT) are considered the optimal form of evidence, there are relatively few in surgery. Surgical RCT are particularly likely to be discontinued with poor recruitment cited as a leading reason. Surgical RCT present challenges over and above those seen in drug trials as the treatment under study may vary between procedures, between surgeons in one unit, and between units in multi-centred RCT. The most contentious and debated area of vascular access remains the role of arteriovenous grafts, and thus the quality of the data that is used to support opinions, guidelines and recommendations is critical. The aim of this review was to determine the extent of variation in the planning and recruitment in all RCT involving AVG. The findings of this are stark: there have been only 31 RCT performed in 31 years, the vast majority of which exhibited major limitations severe enough to undermine the results. This underlines the need for better quality RCT and data, and further inform the design of future studies. Perhaps most fundamental is the planning for a RCT that accounts for the intended population, the uptake of a RCT and the attrition for the significant co-morbidity in this population.

Dynamic and Static Vessel Malperfusion as a Consequence of Acute Type B Aortic Dissection.

BACKGROUND: Acute type B aortic dissection (TBAD) is relatively uncommon with an estimated incidence of up to 8 cases per 100,000 individuals annually. It can be classified based on presenting clinical and radiological features into complicated and uncomplicated. Following the initial tear, the direction and extent of the dissection flap is unpredictable, possibly propagating proximally or distally. One consequence of a dissection flap is the occurrence of organ malperfusion by occlusion of the origin of the branch vessel. The 2 types of malperfusion in TBAD are static and dynamic, with the latter being the more common mechanism. Thoracic endovascular aortic repair (TEVAR) has demonstrated its high safety and efficacy when used for TBAD and subsequent malperfusion. AIMS: This original study specifically examines patients diagnosed with acute TBAD and treated with TEVAR at a single vascular unit, focusing on those presenting with organ malperfusion. METHODS: Over 16 years, 28 TBAD patients were admitted to a single center and treated using TEVAR. After clinical examination, all patients underwent computed tomography of the thorax and abdomen/pelvis to confirm the diagnosis and classify the extent of the dissection proximally and distally. Once diagnosed, patients were transferred to the high dependency unit and started on blood pressure medication. Subsequent computed tomography scans were performed to classify patients, after which TEVAR was performed. RESULTS: Twenty five patients underwent TEVAR for TBAD, of which 8 (32%) had symptoms of organ malperfusion. The majority of cases presented with hypertension (89%), describing a sudden onset of upper/midthoracic pain. The origin of the left subclavian artery was occluded in 14 (56%) patients with 9 (64%) needing an extra-anatomical bypass. There was only a single mortality due to a posterior circulation stroke 2 days after TEVAR. Median (range) length of coverage of thoracic aorta by the stent-graft was 33 (15-35) cm. The true lumen (TL) perfused the celiac artery in 6/8 malperfusion patients, superior mesenteric artery in 7/8, right renal artery in 6/8, and, conversely, left renal artery in only 2/8. CONCLUSIONS: Complicated TBADs behave in an unpredictable manner as it seems the propagating intimal flap invariably maintains vital organ perfusion via the TL. Maintenance of abdominal vessels perfusion from the TL following TEVAR is vital to ensuring optimal results.

A narrative review of the surgical management of Paget-Schroetter syndrome: case series and long-term follow-up.

Background and Objective: Paget-Schroetter syndrome (PSS) is an uncommon disorder which causes thrombosis of the subclavian vein (SV). This is due to compression of the SV by the surrounding anatomical structures. The optimal management of PSS remains subject to debate, with endovascular intervention and open surgical decompression being favoured current options. This review article evaluates both approaches to the management of PSS, while also presenting a case series with long-term follow-up of patients that underwent open surgical intervention for PSS. Methods: The clinical outcomes of PSS patients undergoing different 4 surgical approaches to perform surgical decompression are included. A literature review, across publications from PubMed, Embase, and Web of Science, was conducted with specific criteria to facilitate evaluation of both open surgical and endovascular approaches to the management of PSS. Key Content and Findings: Evaluation of data from the included case series and available literature suggests that endovascular thrombolytic devices offer better clinical results, however, SV decompression is still required for successful resolution. Conclusions: An approach to PSS encompassing endovascular intervention followed by surgical anatomical decompression may provide optimal outcomes as both intrinsic lesions and extrinsic compression of the SV is treated. However, further prospective investigation into this field is warranted.

Pre-deployment assessment of an AI model to assist radiologists in chest X-ray detection and identification of lead-less implanted electronic devices for pre-MRI safety screening: realized implementation needs and proposed operational solutions.

Purpose: Chest X-ray (CXR) use in pre-MRI safety screening, such as for lead-less implanted electronic device (LLIED) recognition, is common. To assist CXR interpretation, we "pre-deployed" an artificial intelligence (AI) model to assess (1) accuracies in LLIED-type (and consequently safety-level) identification, (2) safety implications of LLIED nondetections or misidentifications, (3) infrastructural or workflow requirements, and (4) demands related to model adaptation to real-world conditions. Approach: A two-tier cascading methodology for LLIED detection/localization and identification on a frontal CXR was applied to evaluate the performance of the original nine-class AI model. With the unexpected early appearance of LLIED types during simulated real-world trialing, retraining of a newer 12-class version preceded retrialing. A zero footprint (ZF) graphical user interface (GUI)/viewer with DICOM-based output was developed for inference-result display and adjudication, supporting end-user engagement and model continuous learning and/or modernization. Results: During model testing or trialing using both the nine-class and 12-class models, robust detection/localization was consistently 100%, with mAP 0.99 from fivefold cross-validation. Safety-level categorization was high during both testing ( AUC ≥ 0.98 and ≥ 0.99 , respectively) and trialing (accuracy 98% and 97%, respectively). LLIED-type identifications by the two models during testing (1) were 98.9% and 99.5% overall correct and (2) consistently showed AUC ≥ 0.92 (1.00 for 8/9 and 9/12 LLIED-types, respectively). Pre-deployment trialing of both models demonstrated overall type-identification accuracies of 94.5% and 95%, respectively. Of the small number of misidentifications, none involved MRI-stringently conditional or MRI-unsafe types of LLIEDs. Optimized ZF GUI/viewer operations led to greater user-friendliness for radiologist engagement. Conclusions: Our LLIED-related AI methodology supports (1) 100% detection sensitivity, (2) high identification (including MRI-safety) accuracy, and (3) future model deployment with facilitated inference-result display and adjudication for ongoing model adaptation to future real-world experiences.

Artificial intelligence for radiological paediatric fracture assessment: a systematic review.

BACKGROUND: Majority of research and commercial efforts have focussed on use of artificial intelligence (AI) for fracture detection in adults, despite the greater long-term clinical and medicolegal implications of missed fractures in children. The objective of this study was to assess the available literature regarding diagnostic performance of AI tools for paediatric fracture assessment on imaging, and where available, how this compares with the performance of human readers. MATERIALS AND METHODS: MEDLINE, Embase and Cochrane Library databases were queried for studies published between 1 January 2011 and 2021 using terms related to 'fracture', 'artificial intelligence', 'imaging' and 'children'. Risk of bias was assessed using a modified QUADAS-2 tool. Descriptive statistics for diagnostic accuracies were collated. RESULTS: Nine eligible articles from 362 publications were included, with most (8/9) evaluating fracture detection on radiographs, with the elbow being the most common body part. Nearly all articles used data derived from a single institution, and used deep learning methodology with only a few (2/9) performing external validation. Accuracy rates generated by AI ranged from 88.8 to 97.9%. In two of the three articles where AI performance was compared to human readers, sensitivity rates for AI were marginally higher, but this was not statistically significant. CONCLUSIONS: Wide heterogeneity in the literature with limited information on algorithm performance on external datasets makes it difficult to understand how such tools may generalise to a wider paediatric population. Further research using a multicentric dataset with real-world evaluation would help to better understand the impact of these tools.

MR Elastography of Abdominal Aortic Aneurysms: Relationship to Aneurysm Events.

Background Abdominal aortic aneurysm (AAA) diameter remains the standard clinical parameter to predict growth and rupture. Studies suggest that using solely AAA diameter for risk stratification is insufficient. Purpose To evaluate the use of aortic MR elastography (MRE)-derived AAA stiffness and stiffness ratio at baseline to identify the potential for future aneurysm rupture or need for surgical repair. Materials and Methods Between August 2013 and March 2019, 72 participants with AAA and 56 healthy participants were enrolled in this prospective study. MRE examinations were performed to estimate AAA stiffness and the stiffness ratio between AAA and its adjacent remote normal aorta. Two Cox proportional hazards models were used to assess AAA stiffness and stiffness ratio for predicting aneurysmal events (subsequent repair, rupture, or diameter >5.0 cm). Log-rank tests were performed to determine a critical stiffness ratio suggesting high-risk AAAs. Baseline AAA stiffness and stiffness ratio were studied using Wilcoxon rank-sum tests between participants with and without aneurysmal events. Spearman correlation was used to investigate the relationship between stiffness and other potential imaging markers. Results Seventy-two participants with AAA (mean age, 71 years ± 9 [SD]; 56 men and 16 women) and 56 healthy participants (mean age, 42 years ± 16; 27 men and 29 women) were evaluated. In healthy participants, aortic stiffness positively correlated with age (ρ = 0.44; P < .001). AAA stiffness (event group [n = 21], 50.3 kPa ± 26.5 [SD]; no-event group [n = 21], 86.9 kPa ± 52.6; P = .01) and the stiffness ratio (event group, 0.7 ± 0.4; no-event group, 2.0 ± 1.4; P < .001) were lower in the event group than the no-event group at a mean follow-up of 449 days. AAA stiffness did not correlate with diameter in the event group (ρ = -0.06; P = .68) or the no-event group (ρ = -0.13; P = .32). AAA stiffness was inversely correlated with intraluminal thrombus area (ρ = -0.50; P = .01). Conclusion Lower abdominal aortic aneurysm stiffness and stiffness ratio measured with use of MR elastography was associated with aneurysmal events at a 15-month follow-up. © RSNA, 2022 See also the editorial by Sakuma in this issue.

The fate of the left subclavian artery in TEVAR for aortic arch pathology.

BACKGROUND AND AIM OF STUDY: The origin of the vertebral artery (VA) from the left subclavian (LSA) is variable and must be considered when proximal ligation or embolization is performed post thoracic endovascular aortic repair (TEVAR) and extra-anatomical bypass (EAB). A retrospective study was conducted to understand the patency of the LSA and VAs after TEVAR and the relationship of the EAB to the LSA. METHODS: Fifty-six patients underwent TEVAR where the LSA origin was occluded. A comparison was performed between the length of the proximal LSA from the arch of the aorta to the origin of the VA. Patient outcomes included posterior or anterior circulation cerebrovascular accident, spinal cord ischemia (SCI), and symptoms and signs of left arm ischemia (LAI). Thirty one underwent EAB with 8 undergoing occlusion of the LSA proximal to the origin of the left VA. A further 25 underwent TEVAR with no EAB performed. The mean (standard deviation) of origin of the VA from the origin at the arch was 37.0 (12.9) mm compared to 34.0 (13.7) mm in those where no bypass was performed (p 0.45). Four patients underwent intraluminal plug occlusion and four had external ligation of the proximal LSA in those undergoing EAB. CONCLUSIONS: Careful evaluation of the LSA is needed when planning TEVAR as occlusion techniques may be dependent on a minimum length of the VA from the aortic arch. The mean length of the VA from the aorta has high heterogeneity which may dictate the optimum occlusion method for LSA.

Renal Arteries Revisited: Anatomy, Pathologic Entities, and Implications for Endovascular Management.

The renal arteries (RAs) are important vessels that usually arise from the abdominal aorta and supply the kidneys; thus, these arteries play a vital role in physiologic functions such as hemofiltration and blood pressure regulation. An understanding of the basis for embryologic development and the frequently variable anatomy of the RAs is necessary to fully appreciate the range of diseases and the implications for procedural planning. Hemorrhage from an RA is relatively common and is typically traumatic or spontaneous, with the latter form often seen in association with underlying tumors or arteriopathy. Accurate diagnostic evaluation of RA disease due to conditions such as atherosclerosis, fibromuscular dysplasia, vasculitis, aneurysm, arteriovenous shunt, embolic disease, and dissection is dependent on the use of multimodality imaging and is essential for selecting appropriate clinical management, with endovascular therapy having a key role in treatment. Surgical considerations include extra-anatomic renal bypass, which remains an important treatment option even in this era of endovascular therapy, and RA embolization as an adjunct to tumor surgery. A novel area of research interest is the potential role of RA denervation in the management of refractory hypertension. ©RSNA, 2021.

Constrained generative adversarial network ensembles for sharable synthetic medical images.

Purpose: Sharing medical images between institutions, or even inside the same institution, is restricted by various laws and regulations; research projects requiring large datasets may suffer as a result. These limitations might be addressed by an abundant supply of synthetic data that (1) are representative (i.e., the synthetic data could produce comparable research results as the original data) and (2) do not closely resemble the original images (i.e., patient privacy is protected). We introduce a framework that generates data with these requirements leveraging generative adversarial network (GAN) ensembles in a controlled fashion. Approach: To this end, an adaptive ensemble scaling strategy with the objective of representativeness is defined. A sampled Fréchet distance-based constraint was then created to eliminate poorly converged candidates. Finally, a mutual information-based validation metric was embedded into the framework to confirm there are visual differences between the original and the generated synthetic images. Results: The applicability of the solution is demonstrated with a case study for generating three-dimensional brain metastasis (BM) from T1-weighted contrast-enhanced MRI studies. A previously published BM detection system was reported to produce 9.12 false-positives at 90% detection sensitivity based on the original data. By using the synthetic data generated with the proposed framework, the system produced 9.53 false-positives at the same sensitivity level. Conclusions: Achieving comparable algorithm performance relying solely on synthetic data unveils a significant potential to eliminate/reduce patient privacy concerns when sharing data in medical imaging.

Artificial Intelligence to Assist in Exclusion of Coronary Atherosclerosis During CCTA Evaluation of Chest Pain in the Emergency Department: Preparing an Application for Real-world Use.

Coronary computed tomography angiography (CCTA) evaluation of chest pain patients in an emergency department (ED) is considered appropriate. While a "negative" CCTA interpretation supports direct patient discharge from an ED, labor-intensive analyses are required, with accuracy in jeopardy from distractions. We describe the development of an artificial intelligence (AI) algorithm and workflow for assisting qualified interpreting physicians in CCTA screening for total absence of coronary atherosclerosis. The two-phase approach consisted of (1) phase 1-development and preliminary testing of an algorithm for vessel-centerline extraction classification in a balanced study population (n = 500 with 50% disease prevalence) derived by retrospective random case selection, and (2) phase 2-simulated clinical Trialing of developed algorithm on a per-case (entire coronary artery tree) basis in a more "real-world" study population (n = 100 with 28% disease prevalence) from an ED chest pain series. This allowed pre-deployment evaluation of the AI-based CCTA screening application which provides vessel-by-vessel graphic display of algorithm inference results integrated into a clinically capable viewer. Algorithm performance evaluation used area under the receiver operating characteristic curve (AUC-ROC); confusion matrices reflected ground truth vs AI determinations. The vessel-based algorithm demonstrated strong performance with AUC-ROC = 0.96. In both phase 1 and phase 2, independent of disease prevalence differences, negative predictive values at the case level were very high at 95%. The rate of completion of the algorithm workflow process (96% with inference results in 55-80 s) in phase 2 depended on adequate image quality. There is potential for this AI application to assist in CCTA interpretation to help extricate atherosclerosis from chest pain presentations.

When is extra-anatomical bypass for the left subclavian artery required to prevent ischaemia after thoracic endovascular stent grafting?

INTRODUCTION: Thoracic endovascular aortic repair (TEVAR) has become an accepted treatment for thoracic aortic disease. However, the principal complications relate to coverage of the thoracic aortic wall and deliberate occlusion of aortic branches over a potentially long segment. Complications include risk of stroke, spinal cord ischaemia (SCI) and arterial insufficiency to the left arm (left arm ischaemia (LAI)). This study specifically scrutinised the development of SCI and LAI after TEVAR for interventions for thoracic aortic disease from 1999 to 2020. In particular, those who underwent extra-anatomical bypass (both immediate and late) were compared to the length of thoracic aortic coverage by the stent graft. MATERIALS AND METHODS: Ninety-eight patients underwent TEVAR. The presenting symptoms, pathology, procedural and follow-up data were collected prospectively with particular evidence of stroke, SCI and LAI both immediate onset and after 48 h of graft placement. RESULTS: Fifty underwent TEVAR for an aneurysm (thoracoabdominal aortic aneurysm), 22 for dissection, 19 for acute transection and 7 for intramural haematoma/pseudoaneurysm of the thoracic aorta. Twenty-nine (30%) required a debranching procedure to increase the proximal landing zone (1 aorto-carotid subclavian bypass, 10 carotid/carotid subclavian bypass and 18 carotid/subclavian bypass). Ten patients (10%) died within 30 days of TEVAR. Twenty-four grafts covered the left subclavian artery origin without a carotid/subclavian bypass. Five required a delayed carotid/subclavian bypass for LAI (4) and SCI (1). Six developed immediate signs of SCI after TEVAR and these 11 (group i) had a mean (SD) length of coverage of the thoracic aorta of 30.2 (10.6) cm compared to 21.5 (11.2) cm (group g) in those who had no LAI or SCI post TEVAR, p < 0.05. CONCLUSIONS: In this series, delayed carotid/subclavian bypass may be required for chronic arm ischaemia and less so for SCI. The length of coverage of thoracic aorta during TEVAR is a factor in the development of delayed SCI and LAI occurrence. Carotid subclavian bypass is required for certain patients undergoing TEVAR (particularly if greater than 20 cm of thoracic aorta is covered).

Predicting Mental Decline Rates in Mild Cognitive Impairment From Baseline MRI Volumetric Data.

PURPOSE: In mild cognitive impairment (MCI), identifying individuals at high risk for progressive cognitive deterioration can be useful for prognostication and intervention. This study quantitatively characterizes cognitive decline rates in MCI and tests whether volumetric data from baseline magnetic resonance imaging (MRI) can predict accelerated cognitive decline. METHODS: The authors retrospectively examined Alzheimer Disease Neuroimaging Initiative data to obtain serial Mini-Mental Status Exam (MMSE) scores, diagnoses, and the following baseline MRI volumes: total intracranial volume, whole-brain and ventricular volumes, and volumes of the hippocampus, entorhinal cortex, fusiform gyrus, and medial temporal lobe. Subjects with <24 months or <4 measurements of MMSE data were excluded. Predictive modeling of fast cognitive decline (defined as >0.6/year) from baseline volumetric data was performed on subjects with MCI using a single hidden layer neural network. RESULTS: Among 698 baseline MCI subjects, the median annual decline in the MMSE score was 1.3 for converters to dementia versus 0.11 for stable MCI (P<0.001). A 0.6/year threshold captured dementia conversion with 82% accuracy (sensitivity 79%, specificity 85%, area under the receiver operating characteristic curve 0.88). Regional volumes on baseline MRI predicted fast cognitive decline with a test accuracy of 71%. DISCUSSION: An MMSE score decrease of >0.6/year is associated with MCI-to-dementia conversion and can be predicted from baseline MRI.

Magnetic resonance elastography for estimating in vivo stiffness of the abdominal aorta using cardiac-gated spin-echo echo-planar imaging: a feasibility study.

INTRODUCTION: Magnetic resonance elastography (MRE)-derived aortic stiffness is a potential biomarker for multiple cardiovascular diseases. Currently, gradient-recalled echo (GRE) MRE is a widely accepted technique to estimate aortic stiffness. However, multi-slice GRE MRE requires multiple breath-holds (BHs), which can be challenging for patients who cannot consistently hold their breath. The aim of this study was to investigate the feasibility of a multi-slice spin-echo echo-planar imaging (SE-EPI) MRE sequence for quantifying in vivo aortic stiffness using a free-breathing (FB) protocol and a single-BH protocol. METHOD: On Scanner 1, 25 healthy subjects participated in the validation of FB SE-EPI against FB GRE. On Scanner 2, another 15 healthy subjects were recruited to compare FB SE-EPI with single-BH SE-EPI. Among all volunteers, five participants were studied on both scanners to investigate the inter-scanner reproducibility of FB SE-EPI aortic MRE. Bland-Altman analysis, Lin's concordance correlation coefficient (LCCC) and coefficient of variation (COV) were evaluated. The phase-difference signal-to-noise ratios (PD SNR) were compared. RESULTS: Aortic MRE using FB SE-EPI and FB GRE yielded similar stiffnesses (paired t-test, P = 0.19), with LCCC = 0.97. The FB SE-EPI measurements were reproducible (intra-scanner LCCC = 0.96) and highly repeatable (LCCC = 0.99). The FB SE-EPI MRE was also reproducible across different scanners (inter-scanner LCCC = 0.96). Single-BH SE-EPI scans yielded similar stiffness to FB SE-EPI scans (LCCC = 0.99) and demonstrated a low COV of 2.67% across five repeated measurements. CONCLUSION: Multi-slice SE-EPI aortic MRE using an FB protocol or a single-BH protocol is reproducible and repeatable with advantage over multi-slice FB GRE in reducing acquisition time. Additionally, FB SE-EPI MRE provides a potential alternative to BH scans for patients who have challenges in holding their breath.

Effects of Patient Size and Radiation Dose on Iodine Quantification in Dual-Source Dual-Energy CT.

RATIONALE AND OBJECTIVES: The purpose of this study was to investigate the potential effects of patient size and radiation dose on the accuracy of iodine quantification using dual-source dual-energy computed tomography (CT). MATERIALS AND METHODS: Three phantoms representing different patient sizes were constructed, containing iodine inserts with concentrations from 0 to 20 mg/ml. Dual-energy CT scans were performed at six dose levels from 2 to 30 mGy. Iodine concentrations were measured using a three-material-decomposition algorithm and their accuracy was assessed. RESULTS: In a small phantom, iodine quantification was accurate and consistent at all dose levels. In a medium phantom, minor underestimations were observed, and the results were consistent except at low dose. In the large phantom, more significant underestimation of iodine concentration was observed at higher doses (≥15 mGy), which was attributed to the beam-hardening effect. At lower doses, increasing upward bias was observed in the CT number, leading to significant overestimations of both iodine concentration and fat fraction, which was attributed to the photon-starvation effect. The severity of the latter effect was determined by mA instead of mAs, suggesting that the electronic noise, rather than the quantum noise, was responsible for the bias. Using higher kVp for the low-energy tube was found to alleviate these effects. CONCLUSION: Reliable iodine quantification can be achieved using dual-source CT, but the result can be affected by patient size and dose rate. In large patients, biases may occur due to the beam-hardening and the photon-starvation effects, in which case higher dose rate and higher kVp are recommended to minimize these effects.

Lower limit of iron quantification using dual-energy CT - a phantom study.

PURPOSE: Dual-energy computed tomography (DECT) has been proposed for quantification of hepatic iron concentration (IC). However, the lower limit of quantification (LLOQ) has not been established, limiting the clinical adoption of this technology. In this study, we aim to (a) establish the LLOQ using phantoms and (b) investigate the effects of patient size, dose level, energy combination, and reconstruction method. METHODS: Three phantom sizes and eight vials of ferric nitrate solution with IC ranging from 0 to 10 mg/ml were used. DECT scans were performed at 80/140 and 100/140Sn kVp, and using five different levels of CT dose index (CTDI). An image-domain three-material-decomposition algorithm was used to calculate the IC. The LLOQ was determined based on the coefficient of variation from repeated measurements. RESULTS: The measured IC correlated strongly with the true IC in the small and medium phantoms (R2 of linear regression > 0.99) and moderately in the large phantom (0.8 < R2 <0.9). The LLOQ improved with increased CTDI. At 30 mGy, the LLOQ was found to be 0.50/1.73/6.25 mg/ml in the small/medium/large phantoms, respectively. 80/140Sn kVp resulted in superior LLOQ for all phantom sizes compared to 100/140Sn kVp, primarily due to the difference in their iron enhancement ratios (1.94 and 1.55, respectively). Iterative reconstruction was found to further improve the LLOQ (by ~ 11%), whereas reconstruction kernel smoothness had negligible effect. The LLOQ of iron was significantly higher than that of iodine due to its lack of a useful k-edge and lower enhancement ratio. CONCLUSION: Iron quantification at clinically important levels was achieved in a small- and a medium-sized phantom using DECT, but proved challenging in a large phantom. Wide spectral separation and accurate calibration were found to be critical to the success of the technology.

Are quantitative features of lung nodules reproducible at different CT acquisition and reconstruction parameters?

Consistency and duplicability in Computed Tomography (CT) output is essential to quantitative imaging for lung cancer detection and monitoring. This study of CT-detected lung nodules investigated the reproducibility of volume-, density-, and texture-based features (outcome variables) over routine ranges of radiation dose, reconstruction kernel, and slice thickness. CT raw data of 23 nodules were reconstructed using 320 acquisition/reconstruction conditions (combinations of 4 doses, 10 kernels, and 8 thicknesses). Scans at 12.5%, 25%, and 50% of protocol dose were simulated; reduced-dose and full-dose data were reconstructed using conventional filtered back-projection and iterative-reconstruction kernels at a range of thicknesses (0.6-5.0 mm). Full-dose/B50f kernel reconstructions underwent expert segmentation for reference Region-Of-Interest (ROI) and nodule volume per thickness; each ROI was applied to 40 corresponding images (combinations of 4 doses and 10 kernels). Typical texture analysis metrics (including 5 histogram features, 13 Gray Level Co-occurrence Matrix, 5 Run Length Matrix, 2 Neighboring Gray-Level Dependence Matrix, and 3 Neighborhood Gray-Tone Difference Matrix) were computed per ROI. Reconstruction conditions resulting in no significant change in volume, density, or texture metrics were identified as "compatible pairs" for a given outcome variable. Our results indicate that as thickness increases, volumetric reproducibility decreases, while reproducibility of histogram- and texture-based features across different acquisition and reconstruction parameters improves. To achieve concomitant reproducibility of volumetric and radiomic results across studies, balanced standardization of the imaging acquisition parameters is required.

Ureteric complications and left retroperitoneal abdominal aortic surgery.

BACKGROUND: Open surgery for abdominal aortic aneurysms in the UK is usually performed via a midline transperitoneal incision. However, the left retroperitoneal (RP) approach may be beneficial for juxtarenal abdominal aortic aneurysms and certain physiological reasons. One potential disadvantage is that the left kidney usually requires mobilization anteromedially risking injury to the renal tract and possibly the ureter. METHODS: In this retrospective study, the time of onset, clinical presentation and treatment of left renal tract complications are scrutinized and discussed. Reasons for open aortic surgery as opposed to endovascular repair being undertaken were documented. Also, the aortic cross-clamp positions and type of reconstruction were examined. RESULTS: A total of 208 patients underwent RP aortic surgery for aneurysmal disease. The aortic cross-clamp positions were infrarenal in 115 (55%), suprarenal in 78 (38%) and supra-superior mesenteric artery or supracoeliac in 15 (7%). Two percent (4/208) sustained ureteric complications and all occurred in the upper third of the left ureter. The time of onset of symptoms ranged from 2 to 14 days post-operatively with a median of 3.5. Clinical signs were non-specific including pyrexia, tachycardia and flank pain. CONCLUSION: Ureteric complications following left RP aortic surgery is uncommon and usually occurs in the upper third of the renal tract. Trauma appears to be the most common cause, although ureteric ischaemia can occur but presents later particularly in those with comorbidities.

Predicting rate of cognitive decline at baseline using a deep neural network with multidata analysis.

Purpose: Our study investigates whether a machine-learning-based system can predict the rate of cognitive decline in mildly cognitively impaired patients by processing only the clinical and imaging data collected at the initial visit. Approach: We built a predictive model based on a supervised hybrid neural network utilizing a three-dimensional convolutional neural network to perform volume analysis of magnetic resonance imaging (MRI) and integration of nonimaging clinical data at the fully connected layer of the architecture. The experiments are conducted on the Alzheimer's Disease Neuroimaging Initiative dataset. Results: Experimental results confirm that there is a correlation between cognitive decline and the data obtained at the first visit. The system achieved an area under the receiver operator curve of 0.70 for cognitive decline class prediction. Conclusion: To our knowledge, this is the first study that predicts "slowly deteriorating/stable" or "rapidly deteriorating" classes by processing routinely collected baseline clinical and demographic data [baseline MRI, baseline mini-mental state examination (MMSE), scalar volumetric data, age, gender, education, ethnicity, and race]. The training data are built based on MMSE-rate values. Unlike the studies in the literature that focus on predicting mild cognitive impairment (MCI)-to-Alzheimer's disease conversion and disease classification, we approach the problem as an early prediction of cognitive decline rate in MCI patients.