Mortality impact of low CAC density predominantly occurs in early atherosclerosis: explainable ML in the CAC consortium

BackgroundMachine learning (ML) models of risk prediction with coronary artery calcium (CAC) and CAC characteristics exhibit high performance, but are not inherently interpretable.ObjectivesTo determine the direction and magnitude of impact of CAC characteristics on 10-year all-cause mortality (ACM) with explainable ML.MethodsWe analyzed asymptomatic subjects in the CAC consortium. We trained ML models on 80% and tested on 20% of the data with XGBoost, using clinical characteristics ?+ ?CAC (ML 1) and additional CAC characteristics of CAC density and number of calcified vessels (ML 2). We applied SHAP, an explainable ML tool, to explore the relationship of CAC and CAC characteristics with 10-year all-cause and CV mortality.Results2376 deaths occurred among 63,215 patients [68% male, median age 54 (IQR 47–61), CAC 3 (IQR 0–94.3)]. ML2 was similar to ML1 to predict all-cause mortality (Area Under the Curve (AUC) 0.819 vs 0.821, p ?= ?0.23), but superior for CV mortality (0.847 vs 0.845, p ?= ?0.03).Low CAC density increased mortality impact, particularly ≤0.75. Very low CAC density ≤0.75 was present in only 4.3% of the patients with measurable density, and 75% occurred in CAC1-100. The number of diseased vessels did not increase mortality overall when simultaneously accounting for CAC and CAC density.ConclusionCAC density contributes to mortality risk primarily when it is very low ≤0.75, which is primarily observed in CAC 1–100. CAC and CAC density are more important for mortality prediction than the number of diseased vessels, and improve prediction of CV but not all-cause mortality. Explainable ML techniques are useful to describe granular relationships in otherwise opaque prediction models.     

A multiple domain postural control assessment in people with Parkinson’s disease: traditional,non-linear,and rambling and trembling trajectories analysis

BackgroundPostural impairment is one of the most debilitating symptoms in people with Parkinson's disease (PD), which show faster and more variable oscillation during quiet stance than neurologically healthy individuals. Despite the center of pressure parameters can characterize PD’s body sway, they are limited to uncover underlying mechanisms of postural stability and instability.Research questionDo a multiple domain analysis, including postural adaptability and rambling and trembling components, explain underlying postural stability and instability mechanisms in people with PD?MethodTwenty-four individuals (12 people with PD and 12 neurologically healthy peers) performed three 60-s trials of upright quiet standing on a force platform. Traditional and non-linear parameters (Detrended Fluctuation Analysis- DFA and Multiscale Entropy- MSE) and rambling and trembling trajectories were calculated for anterior-posterior (AP) and medial-lateral (ML) directions.ResultsPDG’s postural control was worse compared to CG, displaying longer displacement, higher velocity, and RMS. Univariate analyses revealed largely longer displacement and RMS only for the AP direction and largely higher velocity for both AP and ML directions. Also, PD individuals showed lower AP complexity, higher AP and ML DFA, and increased AP and ML displacement, velocity, and RMS of rambling and trembling components compared to neurologically healthy individuals.SignificanceBased upon these results, people with PD have a lower capacity to adapt posture and impaired both rambling and trembling components compared to neurologically healthy individuals. These findings provide new insights to explain the larger, faster, and more variable sway in people with PD.     

Lack of Growth of Small (≤2 mm Feeding Artery) Untreated Pulmonary Arteriovenous Malformations in Patients with Hereditary Hemorrhagic Telangiectasia

PurposeTo assess pulmonary arteriovenous malformation (PAVM) growth among patients with untreated PAVMs using imaging from long-term follow-up per hereditary hemorrhagic telangiectasia international guidelines.Materials and MethodsAnalysis included 88 untreated PAVMs from 21 patients (6 male;15 female; mean age at presentation 47 y; range, 12–68 y). Two CT studies with the longest interval between were evaluated (mean 8.4 y; median 8.8 y; range, 3.1–14.1 y). Measurement of feeding artery diameter and anteroposterior (AP) and mediolateral (ML) sac dimensions for each PAVM was performed separately by 2 radiologists blinded to patient and CT order. Statistical analysis was performed to determine change in size between earliest and follow-up imaging.ResultsMean feeding artery diameter, AP sac dimension, and ML sac dimension were 1.4 mm (range, 0.8–3.7 mm), 4.3 mm (range, 2.1–11.1 mm), and 4.1 mm (range, 1.8–9.2 mm) on earliest imaging and 1.4 mm (range, 0.9–2.6 mm), 4.5 mm (range, 2.2–12.2 mm), and 4.3 mm (range, 2.0–9.6 mm) on follow-up. Model-based mean analysis showed no statistically significant change in dimension of any variable between earliest and follow-up imaging. Secondary analysis including age also found no statistically significant difference (feeding diameter, P = .09; AP sac dimension, P = .9; ML sac dimension, P = .1). Analysis including time between measurements found no significant relationship between change in variables and time (feeding artery diameter, P = .4; AP sac dimension, P = .3; ML sac dimension, P = .06).ConclusionsUntreated PAVMs grew slowly, if at all, in a near-decade span, and any demonstrated growth was minimal. These findings challenge the current recommendation of 3- to 5-year CT follow-up.     

Applying patient characteristics,stent-graft selection,and pre-operative computed tomographic angiography data to a machine learning algorithm: Is endoleak prediction possible?

IntroductionThis study aims to predict endoleak after endovascular aneurysm repair (EVAR) using machine learning (ML) integration of patient characteristics, stent-graft configuration, and a selection of vessel lengths, diameters and angles measured using pre-operative computed tomography angiography (CTA).MethodsWe evaluated 1-year follow-up CT scans (arterial and delayed phases) in patients who underwent EVAR for the presence or absence of an endoleak. We also obtained data on the patient characteristics, stent-graft selection, and preoperative CT vessel morphology (diameter, length, and angle). The extreme gradient boosting (XGBoost) for the ML system was trained on 30 patients with endoleaks and 81 patients without. We evaluated 5217 items in 111 patients with abdominal aortic aneurysms, including the patient characteristics, stent-graft configuration and vascular morphology acquired using pre-EVAR abdominal CTA. We calculated the area under the curve (AUC) of our receiver operating characteristic analysis using the ML method.ResultsThe AUC, accuracy, 95% confidence interval (CI), sensitivity, and specificity were 0.88, 0.88, 0.79–0.97, 0.85, and 0.91 for ML applying XGBoost, respectively.ConclusionsThe diagnostic performance of the ML method was useful when factors such as the patient characteristics, stent-graft configuration and vessel length, diameter and angle of the vessels were considered from pre-EVAR CTA.Implications for practiceBased on our findings, we suggest that this is a potential application of ML for the interpretation of abdominal CTA scans in patients with abdominal aortic aneurysms scheduled for EVAR.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

The Effect of Smoking Cessation on the Technical Success of Endovascular Treatment for Thromboangiitis Obliterans

PurposeTo show that smoking cessation improves the technical success of lower extremity endovascular treatment in patients with thromboangiitis obliterans (TAO), or Buerger disease.Materials and MethodsOne hundred two patients with TAO who underwent endovascular treatment for chronic limb-threatening ischemia or severe claudication of lower extremities in a tertiary hospital between 2015 and 2022 were included in this retrospective study. Data on serum cotinine levels were available for the last 45 patients, and 38 patients constituted the study population. Per the institution’s protocol, patients were instructed to quit smoking 15 days before the intervention. However, cotinine levels showed that some of the patients continued smoking. Technical and recanalization successes were assessed as the primary end points. The secondary end point was the improvement in Rutherford scores at the 1-month follow-up. The McNemar test was used to compare the proportion of recanalized arteries after the intervention.ResultsThirty-seven men and 1 woman (mean age, 42.9 years ± 10.1) were evaluated. The overall technical success rate was 86.8% in the study group. The technical success rate was significantly higher in the nonsmoker group (n = 24 [96%]) than in the smoker group (n = 8 [61.5%]; P = .006). One-month clinical data were available for 100% of the patients. The Rutherford category of the nonsmoker group was significantly lower at the 1-month follow-up. In addition, the Wilcoxon signed-rank test revealed lower Rutherford scores after the intervention in the nonsmoker group. The adverse event rate was 8%. One (2.7%) patient in the smoker group underwent a minor amputation.ConclusionsCessation of smoking before endovascular therapy improved technical success and recanalization rates in patients with TAO.     

The effect of different statistical approaches on image quality data obtained from radiological examinations

IntroductionSelection of optimal image acquisition protocols in medical imaging remains a grey area, the superimposed use of the Likert scale in radiological image quality evaluations creates an additional challenge for the statistical analysis of image quality data.Using a simulation study, we have trialled a novel approach to analysing radiological image quality Likert scale data.MethodsA simulation study was undertaken where simulated datasets were generated based on the distribution of Likert scale values according to varying image acquisition protocols from a real dataset. Simulated Likert scale values were pooled in four different ways; the mean, median, mode and the summation of patient Likert scale values of which the total was assigned a categorical Likert scale value. Estimates of bias, MAPE and RMSPE were then calculated for all four pooling approaches to determine which method most accurately represented an expert's opinion.ResultsWhen compared to an expert's opinion, the method of summation and categorisation of Likert scale values was most accurate 49 times out of the 114 (43.0%) tests. The mean 28 times out of 114 (24.6%), the median 23 times out of 114 (20.2%) and the mode 17 times out of 114 (14.9%).ConclusionWe conclude that our method of summation and categorisation of Likert scale values is most often the best representation of the simulated data compared to the expert's opinion.Implications for practiceThere is scope to reproduce this simulation study with multiple observers to reflect clinical reality more accurately with the dynamic nature of multiple observers. This also prompts future investigation into other anatomical areas, to see if the same methods produce similar results.     

Comparing Radiomics features of tumour and healthy liver tissue in a limited CT dataset: A machine learning study

IntroductionLiver cancer lesions on Computed Tomography (CT) withholds a great amount of data, which is not visible to the radiologists and radiographer. Radiomics features can be extracted from the lesions and used to train Machine Learning (ML) algorithms to predict between tumour and liver tissue. The purpose of this study was to investigate and classify Radiomics features extracted from liver tumours and normal liver tissue in a limited CT dataset.MethodsThe Liver Tumour Segmentation Benchmark (LiTS) dataset consisting of 131 CT scans of the liver with segmentations of tumour tissue and healthy liver was used to extract Radiomic features. Extracted Radiomic features included size, shape, and location extracted with morphological and statistical techniques according to the International Symposium on Biomedical Imaging manual. Relevant features was selected with chi2 correlation and principal component analysis (PCA) with tumour and healthy liver tissue as outcome according to a consensus between three experienced radiologists. Logistic regression, random forest and support vector machine was used to train and validate the dataset with a 10-fold cross-validation method and the Grid Search as hyper-parameter tuning. Performance was evaluated with sensitivity, specificity and accuracy.ResultsThe performance of the ML algorithms achieved sensitivities, specificities and accuracy ranging from 96.30% (95% CI: 81.03%–99.91%) to 100.00% (95% CI: 86.77%–100.00%), 91.30% (95% CI: 71.96%–98.93%) to 100.00% (95% CI: 83.89%–100.00%)and 94.00% (95% CI: 83.45%–98.75%) to 100.00% (95% CI: 92.45%–100.00%), respectively.ConclusionML algorithms classifies Radiomics features extracted from healthy liver and tumour tissue with perfect accuracy. The Radiomics signature allows for a prognostic biomarker for hepatic tumour screening on liver CT.Implications for practiceDifferentiation between tumour and liver tissue with Radiomics ML algorithms have the potential to increase the diagnostic accuracy, assist in the decision-making of supplementary multiphasic enhanced medical imaging, as well as for developing novel prognostic biomarkers for liver cancer patients.     

Computed Tomography Angiography Prediction of Successful Trasnscatheter Embolization for Type II Endoleak of Endovascular Abdominal Aortic Aneurysm Repair

PurposeTo evaluate the utility of computed tomography (CT) angiography before transarterial embolization (TAE) in predicting TAE’s technical success for type II endoleaks (T2ELs).Materials and MethodsFifty-eight patients (mean age, 74.4 years; range, 46–89 years) who underwent attempted TAE for T2EL from July 2014 to August 2019 and underwent CT angiography before the procedure were included. Each CT angiography result was assessed for a feeding artery that was traceable over its entire course from either the superior mesenteric artery or the internal iliac artery to the endoleak cavity. TAE was performed using coils and was considered technically successful if embolization of the endoleak cavity and feeding artery was performed. The technical success rates were compared between patients with and without traceable feeding arteries.ResultsA fully traceable feeding artery supplying 75% (44/59) of endoleaks in the cohort was identified. TAE was technically successful in 95% (42/44) of these cases but only in 13% (2/15) of the cases without a fully traceable feeding artery (P < .001). When the inferior mesenteric artery was the feeding artery, it was always fully traceable, and TAE was technically successful in 100% (33/33) of the cases. When a lumbar artery was the feeding artery, it was fully traceable in only 42% (11/26) of the cases. When the lumbar artery was not fully traceable, TAE was technically successful in only 13% (2/15) of the cases.ConclusionsThe traceability of a feeding artery over its entire course to an endoleak cavity using CT angiography was associated with TAE’s technical success. Lumbar feeding arteries were less likely to be fully traceable. TAE’s high failure rate when the feeding artery was not fully traceable suggests that translumbar embolization can be considered as an initial approach for theses patients.     

Dental radiographic information of term newborn babies within the first month: Analyzing five radiographic cases along with physical attributes in Japan

BackgroundAlthough dental radiography is a valuable tool for age estimation in forensic anthropology and odontology, very limited radiological data are available regarding tooth development in healthy newborn babies during the first month of life.AimThis study aimed to describe the radiological findings of tooth development in babies aged 0 days to 1 month.DesignWe analyzed the postmortem findings of five newborn babies with no known natural cause of death who had undergone autopsy, computed tomography (CT), and dental radiography. We estimated the gestational age for the babies aged 0 days and analyzed the condition of mandibular symphysis, existence of tooth germs, and presence or absence of calcification of the first permanent molars of all the babies.ResultsThe calcified form of 20 deciduous teeth, tooth germs of the permanent upper and lower first molars, and non-calcified mandibular symphysis were observed in each case. However, calcification of the first permanent molar was observed in only two 1-month-old babies.ConclusionThe dental radiographic findings and anthropometric measurements of non-skeletonized, non-mummified term babies confirmed calcification of all the deciduous teeth and the first permanent molar at the age of 0 days and 1 month, respectively.     

Computed tomography reference dimensions for identification of stented surgical mitral bioprostheses valve size

BackgroundSelection of the transcatheter heart valve size for a mitral valve-in-valve procedure is based on the type and manufacturer’s labelled size. However, accurate information of surgical heart valve (SHV) size may not be available in the patient’s medical record. The purpose of this study is to establish reference data for computed tomography (CT) dimensions of commonly used mitral SHV in order to determine the manufacturer’s labelled size from a cardiac CT data set.MethodsCT datasets of 105 patients with surgical mitral bioprosthesis and available manufacturer labeled datasets were included in the analysis. CT derived valve dimensions were assessed by two observers using multiplanar reformats aligned with the basal sewing ring. A circular region of interest was used in a standardized fashion to minimize influence of image acquisition and reconstruction parameters. Interobserver variability was assessed by Bland-Altman analysis.ResultsThe CT-derived dimensions were stratified by valve size and type, and SHV properties were demonstrated for 5 common valve types. Variability of measurements was small and inter-observer limits of agreement were narrow. Stratified by SHV type, no overlap was noted for CT-derived dimensions among different SHV sizes . A reference table of CT characteristics of surgical mitral bioprosthesis types was created.ConclusionThe study provides reference CT data for determining the manufacturers’ labeled SHV size across a range of commonly used mitral SHVs. The findings will be important to help identify types of surgical mitral bioprosthesis utilizing CT characteristics for patients without SHV size documentation.     

Thrombotic Risk Associated with Inferior Vena Cava Filter Placement in Patients with Heparin-Induced Thrombocytopenia

PurposeThis study sought to define thromboembolic risk and mortality in patients with heparin-induced thrombocytopenia (HIT) undergoing inferior vena cava filter (IVCF) placement, in light of the American Society of Hematology’s 2018 guidelines against routine use of IVCFs in this population.MethodsA total of 26 patients with HIT who received IVCFs were retrospectively reviewed, and the outcomes of this group were compared with those of 4,707 controls with either HIT or IVCFs alone and with reported outcomes in prior studies.ResultsThe patient group demonstrated 6- and 12-month mortality rates of 26.9% and 30.8%, respectively, which did not differ significantly from those of the control groups and were in line with published mortality rates in the literature. The measured thromboembolic risk of 19.2% in the patient group was also within the range of published rates for patients with HIT or IVCF alone.ConclusionsIVCF placement did not significantly increase the risk of thromboembolism or death in patients with HIT and may be a viable option in the subset of these patients who are not candidates for anticoagulation.     

Outcomes after Peripancreatic Fluid Drainage in Patients with Simultaneous Pancreas-Kidney Transplantation

PurposeTo determine the clinical outcomes of patients who underwent image-guided drainage of peripancreatic fluid collections after simultaneous pancreas-kidney (SPK) transplantation.Materials and MethodsA retrospective review of all patients who underwent peripancreatic fluid collection drainage after SPK, from January 2000 to August 2017, at a single institution was performed. Patient characteristics, surgical technique, medication regimen, microbial analysis, and clinical outcomes were reviewed. Thirty-one patients requiring a total of 41 drainages were included in this study. The median age was 44 years (range 30–58 years), and median time between SPK and drainage was 28 days (range 8 to 3,401 days). Fisher’s exact test, unpaired Student t-tests, and Pearson correlations were used for statistical analysis.ResultsFever (51%) and abdominal pain (31%) were the most common presenting symptoms. The average amount of fluid drained at the time of drain placement was 97 mL (SD 240 mL). The average time spent with a drain in place was 33 days (SD 31 days). Microorganisms were isolated in the fluid of 22 of 41 drainages (54%), with mixed gastrointestinal flora being the most common. No further intervention was needed in 34 of 41 drainages (82%). However, drainage failed in 5 of 31 patients (16%), requiring surgical intervention with removal of the pancreas transplant.ConclusionsPercutaneous drainage of peripancreatic fluid collections after SPK transplantation is a safe and effective treatment option.     

Coronary artery calcium scoring in low risk patients with family history of coronary heart disease: Validation of the SCCT guideline approach in the coronary artery calcium consortium

BackgroundThe Society of Cardiovascular Computed Tomography (SCCT) recommends consideration of coronary artery calcium (CAC) scoring among individuals with a family history (FH) of coronary heart disease (CHD) and atherosclerotic cardiovascular disease (ASCVD) risk <5%. No dedicated study has examined the prognostic significance of CAC scoring among this population.MethodsThe CAC Consortium is a multi-center observational cohort study from four clinical centers linked to long-term follow-up for cause-specific mortality. All CAC scans were physician referred and performed in patients without a history of CHD. Our analysis includes 14,169 patients with ASCVD scores <5% and self-reported FH of CHD.ResultsThis cohort had a mean age of 48.1 (SD 7.4), was 91.3% white, 47.4% female, had an average ASCVD score of 2.3% (SD 1.3), and 59.4% had a CAC = 0. The event rate for all-cause mortality was 1.2 per 1000 person-years, 0.3 per 1000 person-years for CVD-specific mortality, and 0.2 per 1000 person-years for CHD-specific mortality. In multivariable Cox proportional hazard models, those with CAC>100 had a 2.2 (95% CI 1.5–3.3) higher risk of all-cause mortality, 4.3 (95% CI 1.9–9.5) times higher risk of CVD-specific mortality, and a 10.4 (95% CI 3.2–33.7) times higher risk of CHD-specific mortality compared to individuals with CAC = 0. The NNS to detect CAC >100 in this sample was 9.ConclusionIn otherwise low risk patients with FH of CHD, CAC>100 were associated with increased risk of all-cause and CHD mortality with event rates in a range that may benefit with preventive pharmacotherapy. These data strongly support new SCCT recommendations regarding testing of patients with a family history of CHD.     

Radiation Dose during Transarterial Radioembolization: A Dosimetric Comparison of Cone-Beam CT and Angio-CT Technologies

PurposeTo evaluate the radiation dose differences for intraprocedural computed tomography (CT) imaging between cone-beam CT and angio-CT acquired during transarterial radioembolization (TARE) therapies for hepatocellular carcinoma.Materials and MethodsA retrospective cohort of 22 patients who underwent 23 TARE procedures were selected. Patients were imaged in both cone-beam CT and angio-CT rooms as a part of their conventional treatment plan. Effective dose contributions from individual CT acquisitions as well as the cumulative dose contributions from procedural 3D imaging were evaluated. Angiography dose contributions were omitted. Cone-beam CT images were acquired on a C-arm Philips Allura system. Effective doses were evaluated by coupling previously published conversion factors (effective dose per dose-area product) to patient’s dose-area product meter readings after the procedure. Angio-CT images were acquired on a hybrid Canon Infinix-i Aquilion PRIME system. Effective doses from angio-CT scans were estimated using Radimetrics. Comparisons of a single patient’s dose differential between the 2 technologies were made.ResultsThe mean effective dose from a single CT scan was 6.42 mSv and 5.99 mSv in the cone-beam CT room and the angio-CT room, respectively (P = .3224), despite the greater field of view and average craniocaudal scan coverage in angio-CT. The mean effective dose summed across all CTs in a procedure was 12.89 mSv and 34.35 mSv in the cone-beam CT room and the angio-CT room, respectively (P = .0018).ConclusionsThe mean effective dose per CT scan is comparable between cone-beam CT and angio-CT when considered in direct comparison for a single patient.     

Machine Learning Offers Exciting Potential for Predicting Postprocedural Outcomes: A Framework for Developing Random Forest Models in IR

PurposeTo demonstrate that random forest models trained on a large national sample can accurately predict relevant outcomes and may ultimately contribute to future clinical decision support tools in IR.Materials and MethodsPatient data from years 2012–2014 of the National Inpatient Sample were used to develop random forest machine learning models to predict iatrogenic pneumothorax after computed tomography–guided transthoracic biopsy (TTB), in-hospital mortality after transjugular intrahepatic portosystemic shunt (TIPS), and length of stay > 3 days after uterine artery embolization (UAE). Model performance was evaluated with area under the receiver operating characteristic curve (AUROC) and maximum F1 score. The threshold for AUROC significance was set at 0.75.ResultsAUROC was 0.913 for the TTB model, 0.788 for the TIPS model, and 0.879 for the UAE model. Maximum F1 score was 0.532 for the TTB model, 0.357 for the TIPS model, and 0.700 for the UAE model. The TTB model had the highest AUROC, while the UAE model had the highest F1 score. All models met the criteria for AUROC significance.ConclusionsThis study demonstrates that machine learning models may suitably predict a variety of different clinically relevant outcomes, including procedure-specific complications, mortality, and length of stay. Performance of these models will improve as more high-quality IR data become available.     

Quantification of Blood Flow in Dialysis Access Using Custom-Acquisition Protocol and Imaging Methods: A Clinical Validation Study

PurposeTo determine access blood flow (ABF) rate using 2D image sequences acquired with digital subtraction angiography (DSA) and fluoroscopy.Materials and MethodsA total of 23 patients with known or suspected malfunctioning accesses were imaged using 2 filming modes: DSA at 3 or 6 frames/s (F/s), and fluoroscopy at 10 or 15 pulses/s (P/s). ABF rates were quantified using a bolus tracking method based on cross-correlation algorithm and compared with catheter-based thermal dilution (TD) flow measurements. The indicator-dilution curves were fitted with a gamma-variate (GV) curve fitting model to assess the effect on accuracy. Radiation doses were calculated to examine any increased susceptibility to tissue reactions and stochastic effects.ResultsFor DSA images, the absolute percent deviations (mean ± standard error of mean) in computed flow vs TD flow measurements at 3 F/s and 6 F/s were 34% ± 4.5% and 20% ± 4.7%, respectively, without curve fitting, and 31% ± 3.3% and 20% ± 4.1%, respectively, with curve fitting. For fluoroscopic images, the deviations at 10 P/s and 15 P/s were 44% ± 7.3% and 68% ± 10.7%, respectively, without curve fitting and 36% ± 6.4% and 48% ± 7.1%, respectively, with curve fitting. The mean peak skin dose and effective dose at 6 F/s were 3.28 mGy and 75 μSv, respectively.ConclusionsDigital subtraction angiography images obtained at 6 F/s offered the highest accuracy for dialysis access blood flow quantification.     

Comparison of Bolus Versus Dual-Syringe Administration Systems on Glass Yttrium-90 Microsphere Deposition in an In Vitro Microvascular Hepatic Tumor Model

PurposeTo utilize an in vitro microvascular hepatic tumor model to compare the deposition characteristics of glass yttrium-90 microspheres using the dual-syringe (DS) and traditional bolus administration methods.Materials and MethodsThe microvascular tumor model represented a 3.5-cm tumor in a 1,400-cm³ liver with a total hepatic flow of 160 mL/min and was dynamically perfused. A microcatheter was placed in a 2-mm artery feeding the tumor model and 2 additional nontarget arteries. Glass microspheres with a diameter of 20–30 μm were administered using 2 methods: (a) DS delivery at a concentration of 50 mg/mL in either a single, continuous 2-mL infusion or two 1-mL infusions and (b) bolus delivery (BD) of 100 mg of microspheres in a single 3-mL infusion.ResultsOverall, the degree of on-target deposition of the microspheres was 85% ± 11%, with no significant differences between the administration methods. Although the distal penetration into the tumor arterioles was approximately 15 mm (from the second microvascular bifurcation of the tumor model) for all the cases, the distal peak particle counts were significantly higher for the DS delivery case (approximately 5 × 10⁵ microspheres achieving distal deposition vs 2 × 10⁵ for the BD case). This resulted in significantly higher deposition uniformity within the tumor model (90% for the DS delivery case vs 80% for the BD case, α = 0.05).ConclusionsThe use of this new in vitro microvascular hepatic tumor model demonstrated that the administration method can affect the deposition of yttrium-90 microspheres within a tumor, with greater distal deposition and more uniform tumor coverage when the microspheres are delivered at consistent concentrations using a DS delivery device. The BD administration method was associated with less favorable deposition characteristics of the microspheres.     

Prevalence of and Factors Associated with Arterial Aneurysms in Patients with Hereditary Hemorrhagic Telangiectasia: 17-Year Retrospective Series of 418 Patients

PurposeTo estimate the prevalence of and identify characteristics associated with the presence of aneurysms in a cohort of patients with hereditary hemorrhagic telangiectasia (HHT).Materials and MethodsIn the study institution’s HHT database, 418 patients with a definite HHT diagnosis were identified based on the clinical Curaçao criteria and/or an HHT-associated genetic mutation. Regression modeling was used to evaluate the association between arterial aneurysms and older age, male sex, smoking, alcohol consumption, hypertension, hyperlipidemia, genetic mutations, the presence of arteriovenous malformations (AVMs) unrelated to the aneurysms, and HHT-related genetic mutations.ResultsForty-three (10.3%) patients had at least 1 aneurysm. Sixteen (3.8%) patients had multiple aneurysms. Of the variables analyzed, older age (odds ratio [OR] = 1.02; 95% confidence interval [CI]: 1.0–1.1), the presence of anatomically and flow-unrelated AVMs (OR = 3.2; 95% CI: 1.3–8.0), and the presence of activin A receptor type II-like 1 (ACVRL1) mutation (OR = 4.0; 95% CI: 1.5–10) were associated with the presence of at least 1 aneurysm.ConclusionsIn this cohort of patients with HHT, the prevalence of intracranial and visceral arterial aneurysms was estimated to be 10.3%. Older age, the presence of unrelated AVMs, and the presence of the ACVRL1 mutation were associated with the presence of arterial aneurysms. Further study is required to assess the clinical importance and risk of rupture of aneurysms in patients with HHT.